[FreeTutorials.Us] machine-learning-in-python-random-forest-adaboost番号下载_[FreeTutorials.Us] machine-learning-in-python-random-forest-adaboost番号下载_[FreeTutorials.Us] machine-learning-in-python-random-forest-adaboost下载

[FreeTutorials.Us] machine-learning-in-python-random-forest-adaboost

种子简介

种子名称： [FreeTutorials.Us] machine-learning-in-python-random-forest-adaboost
文件类型：视频
文件数目： 34个文件
文件大小： 399.79 MB
收录时间： 2017-12-26 13:16
已经下载： 3次
资源热度： 99
最近下载： 2024-11-7 13:34

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:d6d55155146bc0a0701df35c1de444fa38310e72&dn=[FreeTutorials.Us] machine-learning-in-python-random-forest-adaboost 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

FreeTutorials Us machine-learning-in-python-random-forest-adaboost

种子包含的文件

[FreeTutorials.Us] machine-learning-in-python-random-forest-adaboost.torrent

01 Get Started/001 Outline and Motivation.mp47.19MB

01 Get Started/002 Where to get the Code and Data.mp43.35MB

01 Get Started/003 All Data is the Same.mp45.24MB

01 Get Started/004 Plug-and-Play.mp43.5MB

02 Bias-Variance Trade-Off/005 Bias-Variance Key Terms.mp410.23MB

02 Bias-Variance Trade-Off/006 Bias-Variance Trade-Off.mp44.89MB

02 Bias-Variance Trade-Off/007 Bias-Variance Decomposition.mp45.37MB

02 Bias-Variance Trade-Off/008 Polynomial Regression Demo.mp441.75MB

02 Bias-Variance Trade-Off/009 K-Nearest Neighbor and Decision Tree Demo.mp413.86MB

02 Bias-Variance Trade-Off/010 Cross-Validation as a Method for Optimizing Model Complexity.mp46.97MB

03 Bootstrap Estimates and Bagging/011 Bootstrap Estimation.mp415.17MB

03 Bootstrap Estimates and Bagging/012 Bootstrap Demo.mp410.95MB

03 Bootstrap Estimates and Bagging/013 Bagging.mp43.92MB

03 Bootstrap Estimates and Bagging/014 Bagging Regression Trees.mp415.87MB

03 Bootstrap Estimates and Bagging/015 Bagging Classification Trees.mp420.31MB

03 Bootstrap Estimates and Bagging/016 Stacking.mp46.07MB

04 Random Forest/017 Random Forest Algorithm.mp414.42MB

04 Random Forest/018 Random Forest Regressor.mp414.89MB

04 Random Forest/019 Random Forest Classifier.mp412.58MB

04 Random Forest/020 Random Forest vs Bagging Trees.mp47.82MB

04 Random Forest/021 Implementing a Not as Random Forest.mp48.69MB

04 Random Forest/022 Connection to Deep Learning Dropout.mp44.22MB

05 AdaBoost/023 AdaBoost Algorithm.mp410.88MB

05 AdaBoost/024 Additive Modeling.mp42.78MB

05 AdaBoost/025 AdaBoost Loss Function Exponential Loss.mp411.18MB

05 AdaBoost/026 AdaBoost Implementation.mp415.78MB

05 AdaBoost/027 Comparison to Stacking.mp45.44MB

05 AdaBoost/028 Connection to Deep Learning.mp46.03MB

05 AdaBoost/029 Summary and Whats Next.mp47.37MB

06 Appendix/030 Confidence Intervals.mp415.81MB

06 Appendix/031 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp443.92MB

06 Appendix/032 How to Code by Yourself part 1.mp424.53MB

06 Appendix/033 How to Code by Yourself part 2.mp414.8MB

06 Appendix/034 BONUS Where to get Udemy coupons and FREE deep learning material.mp44.02MB