Hands-On Neural Networks
更新时间：2021-06-24 14:00:47
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Title Page
Copyright and Credits
Hands-On Neural Networks
Dedication
About Packt
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Packt.com
Contributors
About the authors
About the reviewers
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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 color images
Conventions used
Get in touch
Reviews
Section 1: Getting Started
Getting Started with Supervised Learning
History of AI
An overview of machine learning
Supervised learning
Unsupervised learning
Semi-supervised learning
Reinforcement learning
Environment setup
Understanding virtual environments
Anaconda
Docker
Supervised learning in practice with Python
Data cleaning
Feature engineering
How deep learning performs feature engineering
Feature scaling
Feature engineering in Keras
Supervised learning algorithms
Metrics
Regression metrics
Classification metrics
Evaluating the model
TensorBoard
Summary
Neural Network Fundamentals
The perceptron
Implementing a perceptron
Keras
Implementing perceptron in Keras
Feedforward neural networks
Introducing backpropagation
Activation functions
Sigmoid
Softmax
Tanh
ReLU
Keras implementation
The chain rule
The XOR problem
FFNN in Python from scratch
FFNN Keras implementation
TensorBoard
TensorBoard on the XOR problem
Summary
Section 2: Deep Learning Applications
Convolutional Neural Networks for Image Processing
Understanding CNNs
Input data
Convolutional layers
Pooling layers
Stride
Max pooling
Zero padding
Dropout layers
Normalization layers
Output layers
CNNs in Keras
Loading the data
Creating the model
Network configuration
Keras for expression recognition
Optimizing the network
Summary
Exploiting Text Embedding
Machine learning for NLP
Rule-based methods
Understanding word embeddings
Applications of words embeddings
Word2vec
Word embedding in Keras
Pre-trained network
GloVe
Global matrix factorization
Using the GloVe model
Text classification with GloVe
Summary
Working with RNNs
Understanding RNNs
Theory behind CNNs
Types of RNNs
One-to-one
One-to-many
Many-to-many
The same lag
A different lag
Loss functions
Long Short-Term Memory
LSTM architecture
LSTMs in Keras
PyTorch basics
Time series prediction
Summary
Reusing Neural Networks with Transfer Learning
Transfer learning theory
Introducing multi-task learning
Reusing other networks as feature extractors
Implementing MTL
Feature extraction
Implementing TL in PyTorch
Summary
Section 3: Advanced Applications
Working with Generative Algorithms
Discriminative versus generative algorithms
Understanding GANs
Training GANs
GAN challenges
GAN variations and timelines
Conditional GANs
DCGAN
ReLU versus Leaky ReLU
DCGAN – a coded example
Pix2Pix GAN
StackGAN
CycleGAN
ProGAN
StarGAN
StarGAN discriminator objectives
StarGAN generator functions
BigGAN
StyleGAN
Style modules
StyleGAN implementation
Deepfakes
RadialGAN
Summary
Further reading
Implementing Autoencoders
Overview of autoencoders
Autoencoder applications
Bottleneck and loss functions
Standard types of autoencoder
Undercomplete autoencoders
Example
Visualizing with TensorBoard
Visualizing reconstructed images
Multilayer autoencoders
Example
Convolutional autoencoders
Example
Sparse autoencoders
Example
Denoising autoencoders
Example
Contractive autoencoder
Variational Autoencoders
Training VAEs
Example
Summary
Further reading
Deep Belief Networks
Overview of DBNs
BBNs
Predictive propagation
Retrospective propagation
RBMs
RBM training
Example – RBM recommender system
Example – RBM recommender system using code
DBN architecture
Training DBNs
Fine-tuning
Datasets and libraries
Example – supervised DBN classification
Example – supervised DBN regression
Example – unsupervised DBN classification
Summary
Further reading
Reinforcement Learning
Basic definitions
Introducing Q-learning
Learning objectives
Policy optimization
Methods of Q-learning
Playing with OpenAI Gym
The frozen lake problem
Summary
Whats Next?
Summarizing the book
Future of machine learning
Artificial general intelligence
Ethics in AI
Interpretability
Automation
AI safety
AI ethics
Accountability
Conclusions
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更新时间：2021-06-24 14:00:47