{"cells":[{"metadata":{},"cell_type":"markdown","source":"\n# Introduction\n\nMNIST (\"Modified National Institute of Standards and Technology\") is the de facto “hello world” dataset of computer vision. Since its release in 1999, this classic dataset of handwritten images has served as the basis for benchmarking classification algorithms. As new machine learning techniques emerge, MNIST remains a reliable resource for researchers and learners alike. \n\nIn this tutorial, your goal is to correctly identify digits from the Kaggle MNIST dataset of tens of thousands of handwritten images. We will walk through the development process of various ML pipelines using Scikit-Learn to classify handwritten digits to high accuracy."},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\n\nfrom sklearn import metrics, model_selection","execution_count":1,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"%matplotlib inline","execution_count":2,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Load the MNIST data"},{"metadata":{"trusted":true},"cell_type":"code","source":"!head ../input/train.csv","execution_count":3,"outputs":[{"output_type":"stream","text":"label,pixel0,pixel1,pixel2,pixel3,pixel4,pixel5,pixel6,pixel7,pixel8,pixel9,pixel10,pixel11,pixel12,pixel13,pixel14,pixel15,pixel16,pixel17,pixel18,pixel19,pixel20,pixel21,pixel22,pixel23,pixel24,pixel25,pixel26,pixel27,pixel28,pixel29,pixel30,pixel31,pixel32,pixel33,pixel34,pixel35,pixel36,pixel37,pixel38,pixel39,pixel40,pixel41,pixel42,pixel43,pixel44,pixel45,pixel46,pixel47,pixel48,pixel49,pixel50,pixel51,pixel52,pixel53,pixel54,pixel55,pixel56,pixel57,pixel58,pixel59,pixel60,pixel61,pixel62,pixel63,pixel64,pixel65,pixel66,pixel67,pixel68,pixel69,pixel70,pixel71,pixel72,pixel73,pixel74,pixel75,pixel76,pixel77,pixel78,pixel79,pixel80,pixel81,pixel82,pixel83,pixel84,pixel85,pixel86,pixel87,pixel88,pixel89,pixel90,pixel91,pixel92,pixel93,pixel94,pixel95,pixel96,pixel97,pixel98,pixel99,pixel100,pixel101,pixel102,pixel103,pixel104,pixel105,pixel106,pixel107,pixel108,pixel109,pixel110,pixel111,pixel112,pixel113,pixel114,pixel115,pixel116,pixel117,pixel118,pixel119,pixel120,pixel121,pixel122,pixel123,pixel124,pixel125,pixel126,pixel127,pixel128,pixel129,pixel130,pixel131,pixel132,pixel133,pixel134,pixel135,pixel136,pixel137,pixel138,pixel139,pixel140,pixel141,pixel142,pixel143,pixel144,pixel145,pixel146,pixel147,pixel148,pixel149,pixel150,pixel151,pixel152,pixel153,pixel154,pixel155,pixel156,pixel157,pixel158,pixel159,pixel160,pixel161,pixel162,pixel163,pixel164,pixel165,pixel166,pixel167,pixel168,pixel169,pixel170,pixel171,pixel172,pixel173,pixel174,pixel175,pixel176,pixel177,pixel178,pixel179,pixel180,pixel181,pixel182,pixel183,pixel184,pixel185,pixel186,pixel187,pixel188,pixel189,pixel190,pixel191,pixel192,pixel193,pixel194,pixel195,pixel196,pixel197,pixel198,pixel199,pixel200,pixel201,pixel202,pixel203,pixel204,pixel205,pixel206,pixel207,pixel208,pixel209,pixel210,pixel211,pixel212,pixel213,pixel214,pixel215,pixel216,pixel217,pixel218,pixel219,pixel220,pixel221,pixel222,pixel223,pixel224,pixel225,pixel226,pixel227,pixel228,pixel229,pixel230,pixel231,pixel232,pixel233,pixel234,pixel235,pixel236,pixel237,pixel238,pixel239,pixel240,pixel241,pixel242,pixel243,pixel244,pixel245,pixel246,pixel247,pixel248,pixel249,pixel250,pixel251,pixel252,pixel253,pixel254,pixel255,pixel256,pixel257,pixel258,pixel259,pixel260,pixel261,pixel262,pixel263,pixel264,pixel265,pixel266,pixel267,pixel268,pixel269,pixel270,pixel271,pixel272,pixel273,pixel274,pixel275,pixel276,pixel277,pixel278,pixel279,pixel280,pixel281,pixel282,pixel283,pixel284,pixel285,pixel286,pixel287,pixel288,pixel289,pixel290,pixel291,pixel292,pixel293,pixel294,pixel295,pixel296,pixel297,pixel298,pixel299,pixel300,pixel301,pixel302,pixel303,pixel304,pixel305,pixel306,pixel307,pixel308,pixel309,pixel310,pixel311,pixel312,pixel313,pixel314,pixel315,pixel316,pixel317,pixel318,pixel319,pixel320,pixel321,pixel322,pixel323,pixel324,pixel325,pixel326,pixel327,pixel328,pixel329,pixel330,pixel331,pixel332,pixel333,pixel334,pixel335,pixel336,pixel337,pixel338,pixel339,pixel340,pixel341,pixel342,pixel343,pixel344,pixel345,pixel346,pixel347,pixel348,pixel349,pixel350,pixel351,pixel352,pixel353,pixel354,pixel355,pixel356,pixel357,pixel358,pixel359,pixel360,pixel361,pixel362,pixel363,pixel364,pixel365,pixel366,pixel367,pixel368,pixel369,pixel370,pixel371,pixel372,pixel373,pixel374,pixel375,pixel376,pixel377,pixel378,pixel379,pixel380,pixel381,pixel382,pixel383,pixel384,pixel385,pixel386,pixel387,pixel388,pixel389,pixel390,pixel391,pixel392,pixel393,pixel394,pixel395,pixel396,pixel397,pixel398,pixel399,pixel400,pixel401,pixel402,pixel403,pixel404,pixel405,pixel406,pixel407,pixel408,pixel409,pixel410,pixel411,pixel412,pixel413,pixel414,pixel415,pixel416,pixel417,pixel418,pixel419,pixel420,pixel421,pixel422,pixel423,pixel424,pixel425,pixel426,pixel427,pixel428,pixel429,pixel430,pixel431,pixel432,pixel433,pixel434,pixel435,pixel436,pixel437,pixel438,pixel439,pixel440,pixel441,pixel442,pixel443,pixel444,pixel445,pixel446,pixel447,pixel448,pixel449,pixel450,pixel451,pixel452,pixel453,pixel454,pixel455,pixel456,pixel457,pixel458,pixel459,pixel460,pixel461,pixel462,pixel463,pixel464,pixel465,pixel466,pixel467,pixel468,pixel469,pixel470,pixel471,pixel472,pixel473,pixel474,pixel475,pixel476,pixel477,pixel478,pixel479,pixel480,pixel481,pixel482,pixel483,pixel484,pixel485,pixel486,pixel487,pixel488,pixel489,pixel490,pixel491,pixel492,pixel493,pixel494,pixel495,pixel496,pixel497,pixel498,pixel499,pixel500,pixel501,pixel502,pixel503,pixel504,pixel505,pixel506,pixel507,pixel508,pixel509,pixel510,pixel511,pixel512,pixel513,pixel514,pixel515,pixel516,pixel517,pixel518,pixel519,pixel520,pixel521,pixel522,pixel523,pixel524,pixel525,pixel526,pixel527,pixel528,pixel529,pixel530,pixel531,pixel532,pixel533,pixel534,pixel535,pixel536,pixel537,pixel538,pixel539,pixel540,pixel541,pixel542,pixel543,pixel544,pixel545,pixel546,pixel547,pixel548,pixel549,pixel550,pixel551,pixel552,pixel553,pixel554,pixel555,pixel556,pixel557,pixel558,pixel559,pixel560,pixel561,pixel562,pixel563,pixel564,pixel565,pixel566,pixel567,pixel568,pixel569,pixel570,pixel571,pixel572,pixel573,pixel574,pixel575,pixel576,pixel577,pixel578,pixel579,pixel580,pixel581,pixel582,pixel583,pixel584,pixel585,pixel586,pixel587,pixel588,pixel589,pixel590,pixel591,pixel592,pixel593,pixel594,pixel595,pixel596,pixel597,pixel598,pixel599,pixel600,pixel601,pixel602,pixel603,pixel604,pixel605,pixel606,pixel607,pixel608,pixel609,pixel610,pixel611,pixel612,pixel613,pixel614,pixel615,pixel616,pixel617,pixel618,pixel619,pixel620,pixel621,pixel622,pixel623,pixel624,pixel625,pixel626,pixel627,pixel628,pixel629,pixel630,pixel631,pixel632,pixel633,pixel634,pixel635,pixel636,pixel637,pixel638,pixel639,pixel640,pixel641,pixel642,pixel643,pixel644,pixel645,pixel646,pixel647,pixel648,pixel649,pixel650,pixel651,pixel652,pixel653,pixel654,pixel655,pixel656,pixel657,pixel658,pixel659,pixel660,pixel661,pixel662,pixel663,pixel664,pixel665,pixel666,pixel667,pixel668,pixel669,pixel670,pixel671,pixel672,pixel673,pixel674,pixel675,pixel676,pixel677,pixel678,pixel679,pixel680,pixel681,pixel682,pixel683,pixel684,pixel685,pixel686,pixel687,pixel688,pixel689,pixel690,pixel691,pixel692,pixel693,pixel694,pixel695,pixel696,pixel697,pixel698,pixel699,pixel700,pixel701,pixel702,pixel703,pixel704,pixel705,pixel706,pixel707,pixel708,pixel709,pixel710,pixel711,pixel712,pixel713,pixel714,pixel715,pixel716,pixel717,pixel718,pixel719,pixel720,pixel721,pixel722,pixel723,pixel724,pixel725,pixel726,pixel727,pixel728,pixel729,pixel730,pixel731,pixel732,pixel733,pixel734,pixel735,pixel736,pixel737,pixel738,pixel739,pixel740,pixel741,pixel742,pixel743,pixel744,pixel745,pixel746,pixel747,pixel748,pixel749,pixel750,pixel751,pixel752,pixel753,pixel754,pixel755,pixel756,pixel757,pixel758,pixel759,pixel760,pixel761,pixel762,pixel763,pixel764,pixel765,pixel766,pixel767,pixel768,pixel769,pixel770,pixel771,pixel772,pixel773,pixel774,pixel775,pixel776,pixel777,pixel778,pixel779,pixel780,pixel781,pixel782,pixel783\r\r\n1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,188,255,94,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,191,250,253,93,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,123,248,253,167,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80,247,253,208,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,29,207,253,235,77,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54,209,253,253,88,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,93,254,253,238,170,17,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,23,210,254,253,159,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,16,209,253,254,240,81,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,27,253,253,254,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20,206,254,254,198,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,168,253,253,196,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20,203,253,248,76,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22,188,253,245,93,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,103,253,253,191,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,89,240,253,195,25,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,220,253,253,80,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,94,253,253,253,94,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,89,251,253,250,131,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,214,218,95,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,18,30,137,137,192,86,72,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,86,250,254,254,254,254,217,246,151,32,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,16,179,254,254,254,254,254,254,254,254,254,231,54,15,0,0,0,0,0,0,0,0,0,0,0,0,0,0,72,254,254,254,254,254,254,254,254,254,254,254,254,104,0,0,0,0,0,0,0,0,0,0,0,0,0,61,191,254,254,254,254,254,109,83,199,254,254,254,254,243,85,0,0,0,0,0,0,0,0,0,0,0,0,172,254,254,254,202,147,147,45,0,11,29,200,254,254,254,171,0,0,0,0,0,0,0,0,0,0,0,1,174,254,254,89,67,0,0,0,0,0,0,128,252,254,254,212,76,0,0,0,0,0,0,0,0,0,0,47,254,254,254,29,0,0,0,0,0,0,0,0,83,254,254,254,153,0,0,0,0,0,0,0,0,0,0,80,254,254,240,24,0,0,0,0,0,0,0,0,25,240,254,254,153,0,0,0,0,0,0,0,0,0,0,64,254,254,186,7,0,0,0,0,0,0,0,0,0,166,254,254,224,12,0,0,0,0,0,0,0,0,14,232,254,254,254,29,0,0,0,0,0,0,0,0,0,75,254,254,254,17,0,0,0,0,0,0,0,0,18,254,254,254,254,29,0,0,0,0,0,0,0,0,0,48,254,254,254,17,0,0,0,0,0,0,0,0,2,163,254,254,254,29,0,0,0,0,0,0,0,0,0,48,254,254,254,17,0,0,0,0,0,0,0,0,0,94,254,254,254,200,12,0,0,0,0,0,0,0,16,209,254,254,150,1,0,0,0,0,0,0,0,0,0,15,206,254,254,254,202,66,0,0,0,0,0,21,161,254,254,245,31,0,0,0,0,0,0,0,0,0,0,0,60,212,254,254,254,194,48,48,34,41,48,209,254,254,254,171,0,0,0,0,0,0,0,0,0,0,0,0,0,86,243,254,254,254,254,254,233,243,254,254,254,254,254,86,0,0,0,0,0,0,0,0,0,0,0,0,0,0,114,254,254,254,254,254,254,254,254,254,254,239,86,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,182,254,254,254,254,254,254,254,254,243,70,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,76,146,254,255,254,255,146,19,15,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,141,139,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,106,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,185,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,89,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,146,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,156,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,185,255,255,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,185,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,185,254,254,184,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,63,254,254,62,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,220,179,6,0,0,0,0,0,0,0,0,9,77,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,28,247,17,0,0,0,0,0,0,0,0,27,202,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,242,155,0,0,0,0,0,0,0,0,27,254,63,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,160,207,6,0,0,0,0,0,0,0,27,254,65,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,127,254,21,0,0,0,0,0,0,0,20,239,65,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,77,254,21,0,0,0,0,0,0,0,0,195,65,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,70,254,21,0,0,0,0,0,0,0,0,195,142,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,56,251,21,0,0,0,0,0,0,0,0,195,227,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,222,153,5,0,0,0,0,0,0,0,120,240,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,67,251,40,0,0,0,0,0,0,0,94,255,69,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,234,184,0,0,0,0,0,0,0,19,245,69,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,234,169,0,0,0,0,0,0,0,3,199,182,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,154,205,4,0,0,26,72,128,203,208,254,254,131,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,61,254,129,113,186,245,251,189,75,56,136,254,73,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,15,216,233,233,159,104,52,0,0,0,38,254,73,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,18,254,73,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,18,254,73,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,206,106,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,186,159,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,209,101,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,25,130,155,254,254,254,157,30,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,103,253,253,253,253,253,253,253,253,114,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,208,253,253,253,253,253,253,253,253,253,253,107,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,31,253,253,253,253,253,253,253,253,253,253,253,215,101,3,0,0,0,0,0,0,0,0,0,0,0,0,23,210,253,253,253,248,161,222,222,246,253,253,253,253,253,39,0,0,0,0,0,0,0,0,0,0,0,0,136,253,253,253,229,77,0,0,0,70,218,253,253,253,253,215,91,0,0,0,0,0,0,0,0,0,0,5,214,253,253,253,195,0,0,0,0,0,104,224,253,253,253,253,215,29,0,0,0,0,0,0,0,0,0,116,253,253,253,247,75,0,0,0,0,0,0,26,200,253,253,253,253,216,4,0,0,0,0,0,0,0,0,254,253,253,253,195,0,0,0,0,0,0,0,0,26,200,253,253,253,253,5,0,0,0,0,0,0,0,0,254,253,253,253,99,0,0,0,0,0,0,0,0,0,25,231,253,253,253,36,0,0,0,0,0,0,0,0,254,253,253,253,99,0,0,0,0,0,0,0,0,0,0,223,253,253,253,129,0,0,0,0,0,0,0,0,254,253,253,253,99,0,0,0,0,0,0,0,0,0,0,127,253,253,253,129,0,0,0,0,0,0,0,0,254,253,253,253,99,0,0,0,0,0,0,0,0,0,0,139,253,253,253,90,0,0,0,0,0,0,0,0,254,253,253,253,99,0,0,0,0,0,0,0,0,0,78,248,253,253,253,5,0,0,0,0,0,0,0,0,254,253,253,253,216,34,0,0,0,0,0,0,0,33,152,253,253,253,107,1,0,0,0,0,0,0,0,0,206,253,253,253,253,140,0,0,0,0,0,30,139,234,253,253,253,154,2,0,0,0,0,0,0,0,0,0,16,205,253,253,253,250,208,106,106,106,200,237,253,253,253,253,209,22,0,0,0,0,0,0,0,0,0,0,0,82,253,253,253,253,253,253,253,253,253,253,253,253,253,209,22,0,0,0,0,0,0,0,0,0,0,0,0,1,91,253,253,253,253,253,253,253,253,253,253,213,90,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,18,129,208,253,253,253,253,159,129,90,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,141,202,254,193,44,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,165,254,179,163,249,244,72,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,135,254,150,0,0,189,254,243,31,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,82,248,209,5,0,0,164,236,254,115,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,211,254,58,0,0,0,0,33,230,212,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,119,254,156,3,0,0,0,0,18,230,254,33,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,212,254,35,0,0,0,0,0,33,254,254,33,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,116,254,154,3,0,0,0,0,0,33,254,254,33,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,124,254,115,0,0,0,0,0,0,160,254,239,23,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,203,254,35,0,0,0,0,0,0,197,254,178,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,23,239,221,11,0,0,0,0,0,0,198,255,123,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,23,238,178,0,0,0,0,0,0,10,219,254,96,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,30,249,204,0,0,0,0,0,0,25,235,254,62,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,26,243,204,0,0,0,0,0,0,91,254,248,36,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33,254,204,0,0,0,0,0,67,241,254,133,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33,254,214,7,0,0,0,50,242,254,194,24,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,193,254,78,0,0,19,128,254,195,36,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,103,254,222,74,143,235,254,228,83,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,30,242,254,254,254,254,252,84,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,23,64,158,200,174,61,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,82,152,71,51,51,21,41,51,51,51,51,113,193,152,30,0,0,0,0,0,0,0,0,0,0,0,0,0,122,253,252,253,252,223,243,253,252,253,252,253,252,233,30,0,0,0,0,0,0,0,0,0,0,0,0,0,123,102,41,102,102,102,102,102,102,102,162,254,253,142,0,0,0,0,0,0,0,0,0,0,0,0,0,0,203,102,0,0,0,0,0,0,0,0,183,253,212,20,0,0,0,0,0,0,0,0,0,0,0,0,0,0,203,142,0,0,0,0,0,0,0,11,213,254,91,0,0,0,0,0,0,0,0,0,0,0,0,0,0,41,243,102,0,0,0,0,0,0,0,51,252,172,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,41,223,102,0,0,0,0,0,0,0,214,253,102,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20,20,0,0,0,0,0,0,0,253,252,102,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62,254,253,41,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,102,253,171,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,163,254,91,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,203,253,50,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51,253,254,50,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51,252,253,50,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51,253,254,50,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51,252,213,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,152,253,82,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,233,252,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,21,255,253,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20,253,212,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,21,130,190,254,254,250,175,135,96,96,16,4,0,0,0,0,0,0,0,0,0,0,0,0,0,26,102,186,254,254,248,222,222,225,254,254,254,254,254,206,112,4,0,0,0,0,0,0,0,0,0,0,0,207,254,254,177,117,39,0,0,56,248,102,48,48,103,192,254,135,0,0,0,0,0,0,0,0,0,0,0,91,111,36,0,0,0,0,0,72,92,0,0,0,0,12,224,210,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50,139,240,254,66,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,121,220,254,244,194,15,0,0,0,0,0,0,0,0,0,0,0,0,0,8,107,112,112,112,87,112,141,218,248,177,68,20,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,77,221,254,254,254,254,254,225,104,39,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,32,32,32,32,130,215,195,47,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,111,231,174,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,47,18,0,0,0,0,0,0,0,0,0,40,228,205,35,0,0,0,0,0,0,0,0,0,0,0,0,22,234,42,0,0,0,0,0,0,0,0,0,0,56,212,226,38,0,0,0,0,0,0,0,0,0,0,0,96,157,0,0,0,0,0,0,0,0,0,0,0,0,30,215,188,9,0,0,0,0,0,0,0,0,0,0,96,142,0,0,0,0,0,0,0,0,0,0,0,0,0,86,254,68,0,0,0,0,0,0,0,0,0,0,71,202,15,0,0,0,0,0,0,0,0,0,0,0,0,6,214,151,0,0,0,0,0,0,0,0,0,0,10,231,86,2,0,0,0,0,0,0,0,0,0,0,0,0,191,207,0,0,0,0,0,0,0,0,0,0,0,93,248,129,7,0,0,0,0,0,0,0,0,0,0,117,238,112,0,0,0,0,0,0,0,0,0,0,0,0,94,248,209,73,12,0,0,0,0,0,0,42,147,252,136,9,0,0,0,0,0,0,0,0,0,0,0,0,0,48,160,215,230,158,74,64,94,153,223,250,214,105,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,129,189,234,224,255,194,134,75,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,41,149,156,179,254,254,201,119,46,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,147,241,253,253,254,253,253,253,253,245,160,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,31,224,253,253,180,174,175,174,174,174,174,223,247,145,6,0,0,0,0,0,0,0,0,0,0,0,0,7,197,254,253,165,2,0,0,0,0,0,0,12,102,184,16,0,0,0,0,0,0,0,0,0,0,0,0,152,253,254,162,18,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,235,254,158,15,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,74,250,253,15,0,0,0,16,20,19,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,199,253,253,0,0,25,130,235,254,247,145,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20,253,253,177,100,219,240,253,253,254,253,253,125,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,193,253,253,254,253,253,200,155,155,238,253,229,23,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,61,249,254,241,150,30,0,0,0,215,254,254,58,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,36,39,30,0,0,0,0,0,214,253,234,31,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,41,241,253,183,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,201,253,253,102,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,114,254,253,154,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62,254,255,241,30,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,118,235,253,249,103,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55,81,0,102,211,253,253,253,135,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,79,243,234,254,253,253,216,117,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,48,245,253,254,207,126,27,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\r\r\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"mnist_df = pd.read_csv(\"../input/train.csv\", delimiter=',')","execution_count":4,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"mnist_df.head()","execution_count":5,"outputs":[{"output_type":"execute_result","execution_count":5,"data":{"text/plain":"   label  pixel0  pixel1    ...     pixel781  pixel782  pixel783\n0      1       0       0    ...            0         0         0\n1      0       0       0    ...            0         0         0\n2      1       0       0    ...            0         0         0\n3      4       0       0    ...            0         0         0\n4      0       0       0    ...            0         0         0\n\n[5 rows x 785 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>label</th>\n      <th>pixel0</th>\n      <th>pixel1</th>\n      <th>pixel2</th>\n      <th>pixel3</th>\n      <th>pixel4</th>\n      <th>pixel5</th>\n      <th>pixel6</th>\n      <th>pixel7</th>\n      <th>pixel8</th>\n      <th>pixel9</th>\n      <th>pixel10</th>\n      <th>pixel11</th>\n      <th>pixel12</th>\n      <th>pixel13</th>\n      <th>pixel14</th>\n      <th>pixel15</th>\n      <th>pixel16</th>\n      <th>pixel17</th>\n      <th>pixel18</th>\n      <th>pixel19</th>\n      <th>pixel20</th>\n      <th>pixel21</th>\n      <th>pixel22</th>\n      <th>pixel23</th>\n      <th>pixel24</th>\n      <th>pixel25</th>\n      <th>pixel26</th>\n      <th>pixel27</th>\n      <th>pixel28</th>\n      <th>pixel29</th>\n      <th>pixel30</th>\n      <th>pixel31</th>\n      <th>pixel32</th>\n      <th>pixel33</th>\n      <th>pixel34</th>\n      <th>pixel35</th>\n      <th>pixel36</th>\n      <th>pixel37</th>\n      <th>pixel38</th>\n      <th>...</th>\n      <th>pixel744</th>\n      <th>pixel745</th>\n      <th>pixel746</th>\n      <th>pixel747</th>\n      <th>pixel748</th>\n      <th>pixel749</th>\n      <th>pixel750</th>\n      <th>pixel751</th>\n      <th>pixel752</th>\n      <th>pixel753</th>\n      <th>pixel754</th>\n      <th>pixel755</th>\n      <th>pixel756</th>\n      <th>pixel757</th>\n      <th>pixel758</th>\n      <th>pixel759</th>\n      <th>pixel760</th>\n      <th>pixel761</th>\n      <th>pixel762</th>\n      <th>pixel763</th>\n      <th>pixel764</th>\n      <th>pixel765</th>\n      <th>pixel766</th>\n      <th>pixel767</th>\n      <th>pixel768</th>\n      <th>pixel769</th>\n      <th>pixel770</th>\n      <th>pixel771</th>\n      <th>pixel772</th>\n      <th>pixel773</th>\n      <th>pixel774</th>\n      <th>pixel775</th>\n      <th>pixel776</th>\n      <th>pixel777</th>\n      <th>pixel778</th>\n      <th>pixel779</th>\n      <th>pixel780</th>\n      <th>pixel781</th>\n      <th>pixel782</th>\n      <th>pixel783</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# raw features are between 0 and 255\nmnist_df.describe()","execution_count":6,"outputs":[{"output_type":"execute_result","execution_count":6,"data":{"text/plain":"              label   pixel0   pixel1    ...     pixel781  pixel782  pixel783\ncount  42000.000000  42000.0  42000.0    ...      42000.0   42000.0   42000.0\nmean       4.456643      0.0      0.0    ...          0.0       0.0       0.0\nstd        2.887730      0.0      0.0    ...          0.0       0.0       0.0\nmin        0.000000      0.0      0.0    ...          0.0       0.0       0.0\n25%        2.000000      0.0      0.0    ...          0.0       0.0       0.0\n50%        4.000000      0.0      0.0    ...          0.0       0.0       0.0\n75%        7.000000      0.0      0.0    ...          0.0       0.0       0.0\nmax        9.000000      0.0      0.0    ...          0.0       0.0       0.0\n\n[8 rows x 785 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>label</th>\n      <th>pixel0</th>\n      <th>pixel1</th>\n      <th>pixel2</th>\n      <th>pixel3</th>\n      <th>pixel4</th>\n      <th>pixel5</th>\n      <th>pixel6</th>\n      <th>pixel7</th>\n      <th>pixel8</th>\n      <th>pixel9</th>\n      <th>pixel10</th>\n      <th>pixel11</th>\n      <th>pixel12</th>\n      <th>pixel13</th>\n      <th>pixel14</th>\n      <th>pixel15</th>\n      <th>pixel16</th>\n      <th>pixel17</th>\n      <th>pixel18</th>\n      <th>pixel19</th>\n      <th>pixel20</th>\n      <th>pixel21</th>\n      <th>pixel22</th>\n      <th>pixel23</th>\n      <th>pixel24</th>\n      <th>pixel25</th>\n      <th>pixel26</th>\n      <th>pixel27</th>\n      <th>pixel28</th>\n      <th>pixel29</th>\n      <th>pixel30</th>\n      <th>pixel31</th>\n      <th>pixel32</th>\n      <th>pixel33</th>\n      <th>pixel34</th>\n      <th>pixel35</th>\n      <th>pixel36</th>\n      <th>pixel37</th>\n      <th>pixel38</th>\n      <th>...</th>\n      <th>pixel744</th>\n      <th>pixel745</th>\n      <th>pixel746</th>\n      <th>pixel747</th>\n      <th>pixel748</th>\n      <th>pixel749</th>\n      <th>pixel750</th>\n      <th>pixel751</th>\n      <th>pixel752</th>\n      <th>pixel753</th>\n      <th>pixel754</th>\n      <th>pixel755</th>\n      <th>pixel756</th>\n      <th>pixel757</th>\n      <th>pixel758</th>\n      <th>pixel759</th>\n      <th>pixel760</th>\n      <th>pixel761</th>\n      <th>pixel762</th>\n      <th>pixel763</th>\n      <th>pixel764</th>\n      <th>pixel765</th>\n      <th>pixel766</th>\n      <th>pixel767</th>\n      <th>pixel768</th>\n      <th>pixel769</th>\n      <th>pixel770</th>\n      <th>pixel771</th>\n      <th>pixel772</th>\n      <th>pixel773</th>\n      <th>pixel774</th>\n      <th>pixel775</th>\n      <th>pixel776</th>\n      <th>pixel777</th>\n      <th>pixel778</th>\n      <th>pixel779</th>\n      <th>pixel780</th>\n      <th>pixel781</th>\n      <th>pixel782</th>\n      <th>pixel783</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>42000.000000</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.00000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>...</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.00000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.00000</td>\n      <td>42000.000000</td>\n      <td>42000.000000</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n      <td>42000.0</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>4.456643</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00300</td>\n      <td>0.011190</td>\n      <td>0.005143</td>\n      <td>0.000214</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000381</td>\n      <td>0.001310</td>\n      <td>0.010548</td>\n      <td>0.027262</td>\n      <td>0.050905</td>\n      <td>0.066405</td>\n      <td>0.129571</td>\n      <td>...</td>\n      <td>3.772524</td>\n      <td>2.748905</td>\n      <td>1.796452</td>\n      <td>1.089905</td>\n      <td>0.563190</td>\n      <td>0.239571</td>\n      <td>0.093524</td>\n      <td>0.024833</td>\n      <td>0.000857</td>\n      <td>0.001405</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.006143</td>\n      <td>0.035833</td>\n      <td>0.082357</td>\n      <td>0.114905</td>\n      <td>0.178714</td>\n      <td>0.301452</td>\n      <td>0.413643</td>\n      <td>0.513667</td>\n      <td>0.558833</td>\n      <td>0.677857</td>\n      <td>0.60281</td>\n      <td>0.489238</td>\n      <td>0.340214</td>\n      <td>0.219286</td>\n      <td>0.117095</td>\n      <td>0.059024</td>\n      <td>0.02019</td>\n      <td>0.017238</td>\n      <td>0.002857</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>2.887730</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.56812</td>\n      <td>1.626927</td>\n      <td>1.053972</td>\n      <td>0.043916</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.078072</td>\n      <td>0.232634</td>\n      <td>1.131661</td>\n      <td>2.310396</td>\n      <td>3.121847</td>\n      <td>3.259128</td>\n      <td>4.992894</td>\n      <td>...</td>\n      <td>26.957829</td>\n      <td>22.879248</td>\n      <td>18.595109</td>\n      <td>14.434439</td>\n      <td>10.517823</td>\n      <td>6.469315</td>\n      <td>3.976306</td>\n      <td>1.846016</td>\n      <td>0.139556</td>\n      <td>0.287891</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.949803</td>\n      <td>2.350859</td>\n      <td>3.934280</td>\n      <td>4.543583</td>\n      <td>5.856772</td>\n      <td>7.219742</td>\n      <td>8.928286</td>\n      <td>10.004069</td>\n      <td>10.129595</td>\n      <td>11.254931</td>\n      <td>10.69603</td>\n      <td>9.480066</td>\n      <td>7.950251</td>\n      <td>6.312890</td>\n      <td>4.633819</td>\n      <td>3.274488</td>\n      <td>1.75987</td>\n      <td>1.894498</td>\n      <td>0.414264</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>...</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>2.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>...</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>4.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>...</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>7.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>...</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.00000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>9.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>116.00000</td>\n      <td>254.000000</td>\n      <td>216.000000</td>\n      <td>9.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>16.000000</td>\n      <td>47.000000</td>\n      <td>157.000000</td>\n      <td>254.000000</td>\n      <td>255.000000</td>\n      <td>243.000000</td>\n      <td>255.000000</td>\n      <td>...</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>253.000000</td>\n      <td>28.000000</td>\n      <td>59.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>177.000000</td>\n      <td>231.000000</td>\n      <td>253.000000</td>\n      <td>254.000000</td>\n      <td>254.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>255.00000</td>\n      <td>255.000000</td>\n      <td>255.000000</td>\n      <td>254.000000</td>\n      <td>254.000000</td>\n      <td>253.000000</td>\n      <td>253.00000</td>\n      <td>254.000000</td>\n      <td>62.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Rescale the raw data\n\nData for individual pixels is stored as integers between 0 and 255. Neural network models work best when numerical features are scaled. To rescale the raw features we can use tools from the [Scikit-Learn preprocessing module](https://scikit-learn.org/stable/modules/preprocessing.html)."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import preprocessing","execution_count":7,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"training_target, training_features = mnist_df.iloc[:, 0], mnist_df.iloc[:, 1:]","execution_count":8,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"min_max_scaler = preprocessing.MinMaxScaler(feature_range=(0, 1))\nscaled_training_features = min_max_scaler.fit_transform(training_features)","execution_count":9,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/data.py:334: DataConversionWarning: Data with input dtype int64 were all converted to float64 by MinMaxScaler.\n  return self.partial_fit(X, y)\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"_, ax = plt.subplots(1,1)\n_ = ax.imshow(scaled_training_features[0].reshape((28, 28)), cmap=\"gray\")","execution_count":10,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Visualizing training samples"},{"metadata":{},"cell_type":"markdown","source":"## Visualizing training samples using PCA\n\n[Principal Components Analysis (PCA)](https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html) can be used as a visualization tool to see if there are any obvious patterns in the training samples."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import decomposition","execution_count":11,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"decomposition.PCA?","execution_count":12,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"_prng = np.random.RandomState(42)\npca = decomposition.PCA(n_components=2, random_state=_prng)\ntransformed_training_features = pca.fit_transform(scaled_training_features)","execution_count":13,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"fig, ax = plt.subplots(1, 1)\n_ = ax.scatter(transformed_training_features[:,0], transformed_training_features[:,1], c=training_target, alpha=0.05)\nax.set_xlabel(\"Component 1\")\nax.set_ylabel(\"Component 2\")\nax.set_title(\"PCA\", fontsize=20)","execution_count":14,"outputs":[{"output_type":"execute_result","execution_count":14,"data":{"text/plain":"Text(0.5, 1.0, 'PCA')"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Visualizing training sample using t-SNE\n\n[t-distributed Stochastic Neighbor Embedding (t-SNE)](https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html#sklearn.manifold.TSNE) is a tool to visualize high-dimensional data. It converts similarities between data points to joint probabilities and tries to minimize the Kullback-Leibler divergence between the joint probabilities of the low-dimensional embedding and the high-dimensional data. For more details on t-SNE including other use cases see this excellent *Toward Data Science* [blog post](https://towardsdatascience.com/an-introduction-to-t-sne-with-python-example-5a3a293108d1)\n\nIt is highly recommended to use another dimensionality reduction method (e.g. PCA) to reduce the number of dimensions to a reasonable amount if the number of features is very high. This will suppress some noise and speed up the computation of pairwise distances between samples."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import manifold, pipeline","execution_count":15,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"manifold.TSNE?","execution_count":16,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# initial PCA to determine n_components that capture 95% of sample variance\n_prng = np.random.RandomState(42)\npca = decomposition.PCA(random_state=_prng)\npca.fit_transform(scaled_training_features)\nn_components = np.sum(pca.explained_variance_ratio_.cumsum() < 0.95)","execution_count":17,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"As suggested above we will go ahead and use an initial PCA step in our embedding pipeline to reduce the overall number of features which will speed up convergence of the t-SNE algorithm."},{"metadata":{"trusted":true},"cell_type":"code","source":"_prng = np.random.RandomState(42)\n\nembedding_pipeline = pipeline.make_pipeline(\n    decomposition.PCA(n_components, random_state=_prng),\n    manifold.TSNE(n_components=2, random_state=_prng)\n)","execution_count":18,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"_prng = np.random.RandomState(34)\n_n_samples, _ = scaled_training_features.shape\nidxs = _prng.choice(_n_samples, _n_samples // 10, replace=False) ","execution_count":19,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"_sampled_target = training_target[idxs]\n_sampled_features = scaled_training_features[idxs]\n_transformed_sampled_features = embedding_pipeline.fit_transform(_sampled_features)\n\nfig, ax = plt.subplots(1, 1)\n_ = ax.scatter(_transformed_sampled_features[:,0], _transformed_sampled_features[:,1], c=_sampled_target, alpha=0.05)\nax.set_xlabel(\"Component 1\")\nax.set_ylabel(\"Component 2\")\nax.set_title(\"t-SNE\", fontsize=20)","execution_count":20,"outputs":[{"output_type":"execute_result","execution_count":20,"data":{"text/plain":"Text(0.5, 1.0, 't-SNE')"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Classic ML Models"},{"metadata":{"trusted":true},"cell_type":"code","source":"!lscpu","execution_count":21,"outputs":[{"output_type":"stream","text":"Architecture:          x86_64\r\nCPU op-mode(s):        32-bit, 64-bit\r\nByte Order:            Little Endian\r\nCPU(s):                4\r\nOn-line CPU(s) list:   0-3\r\nThread(s) per core:    2\r\nCore(s) per socket:    2\r\nSocket(s):             1\r\nNUMA node(s):          1\r\nVendor ID:             GenuineIntel\r\nCPU family:            6\r\nModel:                 63\r\nModel name:            Intel(R) Xeon(R) CPU @ 2.30GHz\r\nStepping:              0\r\nCPU MHz:               2300.000\r\nBogoMIPS:              4600.00\r\nHypervisor vendor:     KVM\r\nVirtualization type:   full\r\nL1d cache:             32K\r\nL1i cache:             32K\r\nL2 cache:              256K\r\nL3 cache:              46080K\r\nNUMA node0 CPU(s):     0-3\r\nFlags:                 fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm invpcid_single ssbd ibrs ibpb stibp kaiser fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt arat arch_capabilities\r\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"NUMBER_CORES = 4\nNUMBER_THREADS = 2 * NUMBER_CORES","execution_count":22,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Logistic Regression"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import linear_model","execution_count":23,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"linear_model.LogisticRegression?","execution_count":24,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"_prng = np.random.RandomState(42)\nlogistic_regression_clf = linear_model.LogisticRegression(solver=\"lbfgs\",\n                                                          fit_intercept=False,\n                                                          multi_class=\"multinomial\",\n                                                          max_iter=1000,\n                                                          random_state=_prng)\nlogistic_regression_clf.fit(scaled_training_features, training_target)","execution_count":25,"outputs":[{"output_type":"execute_result","execution_count":25,"data":{"text/plain":"LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=False,\n          intercept_scaling=1, max_iter=1000, multi_class='multinomial',\n          n_jobs=None, penalty='l2',\n          random_state=<mtrand.RandomState object at 0x7f95bf15cea0>,\n          solver='lbfgs', tol=0.0001, verbose=0, warm_start=False)"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import model_selection","execution_count":26,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"logistic_regression_clf_accuracy = model_selection.cross_val_score(logistic_regression_clf,\n                                                                   scaled_training_features,\n                                                                   training_target,\n                                                                   scoring=\"accuracy\",\n                                                                   cv=NUMBER_CORES,\n                                                                   n_jobs=NUMBER_CORES,\n                                                                   verbose=10)","execution_count":27,"outputs":[{"output_type":"stream","text":"[Parallel(n_jobs=4)]: Using backend LokyBackend with 4 concurrent workers.\n[Parallel(n_jobs=4)]: Done   1 tasks      | elapsed:  5.2min\n[Parallel(n_jobs=4)]: Done   2 out of   4 | elapsed:  5.3min remaining:  5.3min\n[Parallel(n_jobs=4)]: Done   4 out of   4 | elapsed:  5.4min remaining:    0.0s\n[Parallel(n_jobs=4)]: Done   4 out of   4 | elapsed:  5.4min finished\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"logistic_regression_clf_accuracy.mean()","execution_count":28,"outputs":[{"output_type":"execute_result","execution_count":28,"data":{"text/plain":"0.9167854796151412"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Random Forest Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import ensemble","execution_count":29,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"ensemble.RandomForestClassifier?","execution_count":30,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# evaluate a reasonable classifier using CV\nrandom_forest_clf = ensemble.RandomForestClassifier(n_estimators=100, random_state=_prng, n_jobs=NUMBER_CORES)\nrandom_forest_accuracy = model_selection.cross_val_score(random_forest_clf,\n                                                         scaled_training_features,\n                                                         training_target,\n                                                         scoring=\"accuracy\",\n                                                         cv=NUMBER_CORES,\n                                                         n_jobs=NUMBER_CORES,\n                                                         verbose=10)","execution_count":31,"outputs":[{"output_type":"stream","text":"[Parallel(n_jobs=4)]: Using backend LokyBackend with 4 concurrent workers.\n[Parallel(n_jobs=4)]: Done   1 tasks      | elapsed:   47.2s\n[Parallel(n_jobs=4)]: Done   2 out of   4 | elapsed:   47.7s remaining:   47.7s\n[Parallel(n_jobs=4)]: Done   4 out of   4 | elapsed:   47.9s remaining:    0.0s\n[Parallel(n_jobs=4)]: Done   4 out of   4 | elapsed:   47.9s finished\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"random_forest_accuracy.mean()","execution_count":32,"outputs":[{"output_type":"execute_result","execution_count":32,"data":{"text/plain":"0.9642144203498653"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Submit to Kaggle!\n\n## Make predictions"},{"metadata":{"trusted":true},"cell_type":"code","source":"# retrain the classifier using the entire dataset\nrandom_forest_clf.fit(scaled_training_features, training_target)\n\n# load the testing features (note we use transform method and NOT fit_transform!)\n_testing_features_df = pd.read_csv(\"../input/test.csv\", delimiter=',')\n_scaled_testing_features = min_max_scaler.transform(_testing_features_df)\n\n# make predictions \npredictions = random_forest_clf.predict(_scaled_testing_features)","execution_count":33,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"In order to submit our predictions to Kaggle we first need to produce a correctly formatted submission file."},{"metadata":{"trusted":true},"cell_type":"code","source":"# submission format for kaggle\n!head ../input/sample_submission.csv","execution_count":34,"outputs":[{"output_type":"stream","text":"ImageId,Label\r\r\n1,0\r\r\n2,0\r\r\n3,0\r\r\n4,0\r\r\n5,0\r\r\n6,0\r\r\n7,0\r\r\n8,0\r\r\n9,0\r\r\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"import time\n\nimport pandas as pd\n\ntimestamp = time.strftime(\"%Y%m%d-%H%M%S\")\nnumber_predictions, = predictions.shape\ndf = pd.DataFrame({\"ImageId\": range(1, number_predictions + 1), \"Label\": predictions})\ndf.to_csv(f\"random-forest-submission-{timestamp}.csv\", index=False)","execution_count":35,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Once you have successfully submited your predictions then you can check the [Digit-Recognizer competition](https://www.kaggle.com/c/digit-recognizer) website and see how well your best model compares to your peers."},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.3"}},"nbformat":4,"nbformat_minor":1}