{"blog_url":"https://tokobayashi.hatenablog.com/","title":"Introduction to ML with Python","author_name":"tokobayashi","version":"1.0","width":"100%","type":"rich","description":"Pyhton3 export PATH=\"/home/tkobayas/anaconda3/bin:$PATH\" Jupyter Notebook cd /home/tkobayas/usr/git/amueller/introduction_to_ml_with_python jupyter notebook Supervised Learning Classifier \u3068 Regressor k-NN (k-Nearest Neighbors)k\u500b\u306e\u8fd1\u3044\u3084\u3064\u3092\u62fe\u3046\u3002\u8a13\u7df4\u306f\u30c7\u30fc\u30bf\u3092\u683c\u7d0d\u3059\u308b\u3060\u3051\u3002\u4e88\u6e2c\u306b\u6642\u9593\u304c\u304b\u304b\u308b Linear Regression (ordinary least squar\u2026","published":"2019-04-03 21:20:07","image_url":null,"categories":[],"author_url":"https://blog.hatena.ne.jp/tokobayashi/","height":"190","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Ftokobayashi.hatenablog.com%2Fentry%2F2019%2F04%2F03%2F212007\" title=\"Introduction to ML with Python - tokobayashi\u2019s blog\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","provider_url":"https://hatena.blog","provider_name":"Hatena Blog","blog_title":"tokobayashi\u2019s blog","url":"https://tokobayashi.hatenablog.com/entry/2019/04/03/212007"}