{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.11","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":3004,"databundleVersionId":861823,"sourceType":"competition"}],"dockerImageVersionId":31040,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2025-05-28T22:37:24.410338Z","iopub.execute_input":"2025-05-28T22:37:24.410554Z","iopub.status.idle":"2025-05-28T22:37:24.417837Z","shell.execute_reply.started":"2025-05-28T22:37:24.410536Z","shell.execute_reply":"2025-05-28T22:37:24.417008Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import torch\nimport torch.nn as nn\nimport numpy as np\nimport matplotlib.pyplot as plt","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-28T22:46:32.887483Z","iopub.execute_input":"2025-05-28T22:46:32.888288Z","iopub.status.idle":"2025-05-28T22:46:32.892065Z","shell.execute_reply.started":"2025-05-28T22:46:32.888258Z","shell.execute_reply":"2025-05-28T22:46:32.891241Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# Uploading Data","metadata":{}},{"cell_type":"code","source":"a=\"/kaggle/input/digit-recognizer/sample_submission.csv\"\nb=\"/kaggle/input/digit-recognizer/train.csv\"\nc=\"/kaggle/input/digit-recognizer/test.csv\"\n\na_read= pd.read_csv(a)\nb_read= pd.read_csv(b)\nc_read= pd.read_csv(c)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-28T22:46:33.48373Z","iopub.execute_input":"2025-05-28T22:46:33.484172Z","iopub.status.idle":"2025-05-28T22:46:37.179018Z","shell.execute_reply.started":"2025-05-28T22:46:33.484105Z","shell.execute_reply":"2025-05-28T22:46:37.178084Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# Eda & Some Here and There","metadata":{}},{"cell_type":"code","source":"","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-28T22:47:34.59869Z","iopub.execute_input":"2025-05-28T22:47:34.5991Z","iopub.status.idle":"2025-05-28T22:47:34.605238Z","shell.execute_reply.started":"2025-05-28T22:47:34.599071Z","shell.execute_reply":"2025-05-28T22:47:34.603887Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}