{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"### 학습 목표\n\n- 초대용량 데이터는 어떻게 처리할까요?\n\n\n- 데이터를 분할하여 불러오고 처리하는 방법에 대해서 연습해봅니다.\n\n\n- 불량 검출 문제에 대해 살펴봅니다.\n\n\n- Class imbalance 문제를 해결하는 방법에 대해 알아봅니다.","metadata":{}},{"cell_type":"markdown","source":"## Bosch Production Line Performance\n\n- 공정과정 데이터를 통해 제품 내부 불량 검출하기\n\n- 주어진 공정변수를 이용하여 정상/불량 분류하기","metadata":{"id":"U0IhpuicpE1o"}},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\ntrain = ","metadata":{"id":"improving-limitation","outputId":"874047c9-4bfc-47a0-ee85-24ceb5cf49e1"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### 1. 대용량 데이터 다루기\n\nTechnique1. I/O를 사용해서 chunk 단위로 가져오기\n\n\nTechnique2. nrows와 usecols를 이용해서 데이터 일부를 가져오기","metadata":{}},{"cell_type":"code","source":"# Technique 1.","metadata":{"id":"isolated-barbados"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Technique 2.","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### 2. 불량 검출 문제 다루기 (Class Imbalance problem)\n\nTechnique 1. Sampling Method (Under / Over)\n\nTechnique 2. Hybrid approach","metadata":{}},{"cell_type":"code","source":"# Technique 1.","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Technique 2.","metadata":{},"execution_count":null,"outputs":[]}]}