文件名称：Python-Machine-Learning-By-Example-Third-Edition:Packt发行的Python Machine Learning By Example Third Edition
文件大小：64.08MB
文件格式：ZIP
更新时间：2024-06-15 11:07:37
Python
Python机器学习以示例为例的第三版 Packt发行的Python Machine Learning By Example Third Edition 作者： （Hayden）Liu（ ） 关于这本书 第三版Python Machine Learning By Example配备了最新的更新，它为ML爱好者提供了全面的课程，以增强他们对ML概念，技术和算法的掌握。
【文件预览】：
Python-Machine-Learning-By-Example-Third-Edition-master
----chapter4()
--------avazu_ctr.py(2KB)
--------avazu_ctr_xgboost.py(988B)
--------decision_tree_implementation.py(10KB)
----.gitignore(22B)
----README.md(400B)
----chapter2()
--------naive_bayes.py(4KB)
--------ml-10m.zip(62.53MB)
--------movie_recommendation.py(6KB)
----chapter7()
--------linear_regression.py(4KB)
--------stock_prediction.py(7KB)
--------regression_evaluation.py(1KB)
--------decision_tree_regression.py(7KB)
--------get_dji_data.py(4KB)
--------svr.py(638B)
----chapter14()
--------on_policy_mc_control.py(3KB)
--------taxi_q_learning.py(3KB)
--------simulate_frozenlake.py(1KB)
--------value_iteration.py(3KB)
--------installation.py(318B)
--------mc_policy_evaluation.py(1KB)
--------policy_iteration.py(3KB)
----LICENSE(1KB)
----chapter12()
--------classify_image_augmentation.py(4KB)
--------classify_clothing_image.py(3KB)
----chapter11()
--------generic_feature_engineering.py(529B)
--------word_embedding.py(710B)
--------save_reuse_monitor_model.py(1KB)
--------save_reuse_model_tf.py(769B)
--------dimensionality_reduction.py(809B)
--------feature_selection.py(1KB)
--------imputation.py(3KB)
----chapter9()
--------thinking_about_features.py(1KB)
--------getting_exploring_newsgroups.py(566B)
--------tSNE.py(2KB)
--------exploring_nlp.py(1KB)
----chapter8()
--------neural_network.py(3KB)
--------stock_prediction.py(8KB)
----chapter6()
--------example.py(681B)
--------ctr.py(4KB)
--------ctr_hashing.py(3KB)
--------ctr_interaction.py(3KB)
----chapter13()
--------text_gen_rnn.py(4KB)
--------sentiment_rnn.py(2KB)
--------warpeace_input.txt(3.11MB)
----chapter5()
--------logistic_regression_tf.py(2KB)
--------random_forest_feature_selection.py(1KB)
--------scikit_logistic_regression.py(4KB)
--------logistic_function.py(1KB)
--------logistic_regression_from_scratch.py(6KB)
--------encoding.py(2KB)
----chapter3()
--------CTG.xls(1.66MB)
--------face_recognition_svm.py(2KB)
--------svm_example.py(2KB)
--------ctg.py(1KB)
--------plot_rbf_kernels.py(1KB)
----chapter10()
--------kmeans_elbow.py(909B)
--------lda_newsgroups.py(1KB)
--------kmeans_newsgroups.py(2KB)
--------kmeans_from_scratch.py(2KB)
--------nmf_newsgroups.py(1KB)
--------kmeans_sklearn.py(706B)