更新时间：2021-07-02 15:17:44
coverpage
Title Page
Copyright
Neural Network Programming with TensorFlow
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Why subscribe?
Customer Feedback
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
Maths for Neural Networks
Understanding linear algebra
Environment setup
Setting up the Python environment in Pycharm
Linear algebra structures
Scalars vectors and matrices
Tensors
Operations
Vectors
Matrices
Matrix multiplication
Trace operator
Matrix transpose
Matrix diagonals
Identity matrix
Inverse matrix
Solving linear equations
Singular value decomposition
Eigenvalue decomposition
Principal Component Analysis
Calculus
Gradient
Hessian
Determinant
Optimization
Optimizers
Summary
Deep Feedforward Networks
Defining feedforward networks
Understanding backpropagation
Implementing feedforward networks with TensorFlow
Analyzing the Iris dataset
Code execution
Implementing feedforward networks with images
Analyzing the effect of activation functions on the feedforward networks accuracy
Optimization for Neural Networks
What is optimization?
Types of optimizers
Gradient descent
Different variants of gradient descent
Algorithms to optimize gradient descent
Which optimizer to choose
Optimization with an example
Convolutional Neural Networks
An overview and the intuition of CNN
Single Conv Layer Computation
CNN in TensorFlow
Image loading in TensorFlow
Convolution operations
Convolution on an image
Strides
Pooling
Max pool
Example code
Average pool
Image classification with convolutional networks
Defining a tensor for input images and the first convolution layer
Input tensor
First convolution layer
Second convolution layer
Third convolution layer
Flatten the layer
Fully connected layers
Defining cost and optimizer
Optimizer
First epoch
Plotting filters and their effects on an image
Recurrent Neural Networks
Introduction to RNNs
RNN implementation
Computational graph
RNN implementation with TensorFlow
Introduction to long short term memory networks
Life cycle of LSTM
