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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