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Java Deep Learning Essentials

更新時間：2021-07-16 10:38:54

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ThisbookisintendedfordatascientistsandJavadeveloperswhowanttodiveintotheexcitingworldofdeeplearning.Itwouldalsobegoodformachinelearninguserswhointendtoleveragedeeplearningintheirprojects,workingwithinabigdataenvironment.

目錄(58章)

倒序

coverpage
Java Deep Learning Essentials
Credits
About the Author
About the Reviewers
www.PacktPub.com
eBooks discount offers and more
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Deep Learning Overview
Transition of AI
Things dividing a machine and human
AI and deep learning
Summary
Chapter 2. Algorithms for Machine Learning – Preparing for Deep Learning
Getting started
The need for training in machine learning
Supervised and unsupervised learning
Machine learning application flow
Theories and algorithms of neural networks
Summary
Chapter 3. Deep Belief Nets and Stacked Denoising Autoencoders
Neural networks fall
Neural networks' revenge
Deep learning algorithms
Summary
Chapter 4. Dropout and Convolutional Neural Networks
Deep learning algorithms without pre-training
Dropout
Convolutional neural networks
Summary
Chapter 5. Exploring Java Deep Learning Libraries – DL4J ND4J and More
Implementing from scratch versus a library/framework
Introducing DL4J and ND4J
Implementations with ND4J
Implementations with DL4J
Summary
Chapter 6. Approaches to Practical Applications – Recurrent Neural Networks and More
Fields where deep learning is active
The difficulties of deep learning
The approaches to maximizing deep learning possibilities and abilities
Summary
Chapter 7. Other Important Deep Learning Libraries
Theano
TensorFlow
Caffe
Summary
Chapter 8. What's Next?
Breaking news about deep learning
Expected next actions
Useful news sources for deep learning
Summary
Index 更新時間：2021-07-16 10:38:54

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Java Deep Learning Essentials