Python 数据挖掘入门与实践--代码与文档

[{"title":"（ 31 个子文件 11.88MB ） Python 数据挖掘入门与实践--代码与文档","children":[{"title":"python数据挖掘入门与实践","children":[{"title":"python数据挖掘入门与实践.pdf <span style='color:#111;'> 2.22MB </span>","children":null,"spread":false},{"title":"Chapter 11","children":[{"title":"Chapter 11 (Theano and Lasagne).ipynb <span style='color:#111;'> 60.95KB </span>","children":null,"spread":false},{"title":"Chapter 11 (CIFAR).ipynb <span style='color:#111;'> 57.82KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 9","children":[{"title":"getdata.py <span style='color:#111;'> 3.57KB </span>","children":null,"spread":false},{"title":"Chapter 9 Authorship Analysis.ipynb <span style='color:#111;'> 19.45KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 12","children":[{"title":"extract_posts.py <span style='color:#111;'> 882B </span>","children":null,"spread":false},{"title":"nb_train.py <span style='color:#111;'> 1.97KB </span>","children":null,"spread":false},{"title":"nb_predict.py <span style='color:#111;'> 1.94KB </span>","children":null,"spread":false},{"title":"Chapter 12 (Test load).ipynb <span style='color:#111;'> 1.69KB </span>","children":null,"spread":false},{"title":"CH12 MapReduce Basics.ipynb <span style='color:#111;'> 37.85KB </span>","children":null,"spread":false},{"title":"Chapter 12 (NB Predict).ipynb <span style='color:#111;'> 10.33KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 5","children":[{"title":"ch5_advertisements.ipynb <span style='color:#111;'> 29.28KB </span>","children":null,"spread":false},{"title":"adult_tests.py <span style='color:#111;'> 1.01KB </span>","children":null,"spread":false},{"title":"ch5_adult.ipynb <span style='color:#111;'> 12.98KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 1","children":[{"title":"ch1_oner_application.ipynb <span style='color:#111;'> 13.52KB </span>","children":null,"spread":false},{"title":"affinity_dataset.txt <span style='color:#111;'> 1000B </span>","children":null,"spread":false},{"title":"ch1_affinity_create.ipynb <span style='color:#111;'> 3.58KB </span>","children":null,"spread":false},{"title":"ch1_affinity.ipynb <span style='color:#111;'> 16.38KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 8","children":[{"title":"Sigmoid.ipynb <span style='color:#111;'> 81.03KB </span>","children":null,"spread":false},{"title":"CH8 Rewrite.ipynb <span style='color:#111;'> 286.05KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 3","children":[{"title":"Basketball Results.ipynb <span style='color:#111;'> 44.32KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 6","children":[{"title":"ch6_get_twitter.ipynb <span style='color:#111;'> 13.53KB </span>","children":null,"spread":false},{"title":"ch6_label_twitter.ipynb <span style='color:#111;'> 6.56KB </span>","children":null,"spread":false},{"title":"ch6_classify_twitter.ipynb <span style='color:#111;'> 4.86KB </span>","children":null,"spread":false},{"title":"replicable_dataset.json <span style='color:#111;'> 4.88KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 10","children":[{"title":"Chapter 10 Clusterer.ipynb <span style='color:#111;'> 77.08KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 4","children":[{"title":"ch4 Affinity Analysis.ipynb <span style='color:#111;'> 45.17KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 7","children":[{"title":"ch7_part2_twitter.ipynb <span style='color:#111;'> 544.19KB </span>","children":null,"spread":false},{"title":"CH7 From Load.ipynb <span style='color:#111;'> 11.49MB </span>","children":null,"spread":false},{"title":"ch7_collect_twitter_data.ipynb <span style='color:#111;'> 464.97KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter 2","children":[{"title":"Ionosphere Nearest Neighbour.ipynb <span style='color:#111;'> 139.93KB </span>","children":null,"spread":false}],"spread":true}],"spread":false}],"spread":true}]