Chapter 10: Machine Learning as a Batch Process Chapter 11: Apache Spark Chapter 12: Machine Learning with R I read the book on my Kindle and I did not do the labs but because of illustrations and code listings I had no problems following along. What I thoug...
而不是直接的复制输入到输出- reinforcement learning: 打游戏看了写的代码也觉得这东西没以前那么高深了...3. 代码值得过一遍https://github.com/ageron/handson-ml有时候看书感觉很复杂,看代码反而很简洁而且不断在更新,书中一些错误也在代码中做了补充4. 一些完整的例子(代码)很有学习价值- California Housing...
Chapter 10: Machine Learning as a Batch Process Chapter 11: Apache Spark Chapter 12: Machine Learning with R I read the book on my Kindle and I did not do the labs but because of illustrations and code listings I had no problems following along. ...
Writing an all-encompassing book on Python machine learning is difficult, given how expansive the field is. But reviewing one is not an easy feat either, especially when it’s a highly acclaimed title such asHands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, ...
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To get the most out of this book Get in touch Section 1: Supervised Learning Introduction to Machine Learning Understanding machine learning The model development life cycle Introduction to scikit-learn Installing the packages you need Summary Further reading Making Decisions with Trees Understanding deci...
Hands-On Machine Learning with ML.NET Dedication About Packt Why subscribe? Contributors About the author About the reviewer Packt is searching for authors like you Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the...
learningtechniquestobuildsmartmodels.DeploymachinelearningmodelstoworkonmobileandembeddeddevicesBookDescriptionC++canmakeyourmachinelearningmodelsrunfasterandmoreefficiently.Thishandyguidewillhelpyoulearnthefundamentalsofmachinelearning(ML),showingyouhowtouseC++librariestogetthemostoutofyourdata.Thisbookmakesmachinelearning...