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Advanced Machine Learning with Python

John Hearty 著

更新時間：2021-07-14 10:53:32

開會員，本書免費讀 >

ThistitleisforPythondevelopersandanalystsordatascientistswhoarelookingtoaddtotheirexistingskillsbyaccessingsomeofthemostpowerfulrecenttrendsindatascience.Ifyou’veeverconsideredbuildingyourownimageortext-taggingsolution,orofenteringaKagglecontestforinstance,thisbookisforyou!PriorexperienceofPythonandgroundinginsomeofthecoreconceptsofmachinelearningwouldbehelpful.

目錄(65章)

倒序

封面
版權頁
Credits
About the Author
About the Reviewers
www.PacktPub.com
eBooks discount offers and more
Preface
What is advanced machine learning?
What should you expect from this book?
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Unsupervised Machine Learning
Principal component analysis
Introducing k-means clustering
Self-organizing maps
Further reading
Summary
Chapter 2. Deep Belief Networks
Neural networks – a primer
Restricted Boltzmann Machine
Deep belief networks
Further reading
Summary
Chapter 3. Stacked Denoising Autoencoders
Autoencoders
Stacked Denoising Autoencoders
Further reading
Summary
Chapter 4. Convolutional Neural Networks
Introducing the CNN
Further Reading
Summary
Chapter 5. Semi-Supervised Learning
Introduction
Understanding semi-supervised learning
Semi-supervised algorithms in action
Further reading
Summary
Chapter 6. Text Feature Engineering
Introduction
Text feature engineering
Further reading
Summary
Chapter 7. Feature Engineering Part II
Introduction
Creating a feature set
Feature engineering in practice
Further reading
Summary
Chapter 8. Ensemble Methods
Introducing ensembles
Using models in dynamic applications
Further reading
Summary
Chapter 9. Additional Python Machine Learning Tools
Alternative development tools
Further reading
Summary
Appendix A. Chapter Code Requirements
Index 更新時間：2021-07-14 10:53:32

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Advanced Machine Learning with Python