MakeYourOwnNeuralNetwork_AnIn-depthVisua.epub - (EPUB全文下载)

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Table of Contents
What You’ll Find Inside
Don’t Waste Your Time
Neural Networks
1: What Is A Neural Network?
The Math of Neural Networks: Overview
2: The Math Of Neural Networks: Introduction
3: Basic Terminology And Notation
4: Pre-Stage: Creating the Network
Stage 1: Forward Propagation
5: The Mathematical Functions Used
6: Understanding Matrices
7: Fitting it All Together: Review
Stage 2: Calculating The Total Error
8: Calculating The Total Error
Stage 3: Calculating The Gradients
09: The Mathematical Functions Used
10: Why Gradients Are Important
11: Partial Derivative of Output Layer Weights
12: Partial Derivative of Output Layer Bias Weights
13: Partial Derivative of Hidden Layer Weights
14: Partial Derivative of Hidden Layer Bias Weights
15: Fitting It All Together: Review
Stage 4: Checking The Gradients
16: Numerical Estimation
17: Discovering The Formula
18: Calculating The Numerical Estimation
19: Fitting it All Together: Review
Stage 5: Updating The Weights
20: What is Gradient Descent?
21: Methods of Gradient Descent
22: Updating the Weights
23: Fitting it All Together: Review
Constructing a Network: Hands on Example
24: Defining the Scenario
25: Pre-Stage: Network Structure
26: Stage 1: Running Data Through the Network
27: Stage 2: Calculating the Total Error
28: Stage 3: Calculating the Gradients
29: Stage 4: Gradient Checking
30: Stage 5: Updating the Weights
31: Wrapping it All Up: Final Review
Building Neural Networks in Python
32: The Tools You’ll Need
33: Tensorflow: A Very Brief Overview
34: Tensorflow and Neural Networks: 5 Steps
35: Neural Network: Distinguish Handwriting
36: Neural Network: Classify Images
The History of Neural Networks
30: A Brief History of Neural Networks
Additional Resources
31: Extended Definitions
32: Text Editors and Libraries
Bibliography
What You’ll Find Inside:
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Don’t Waste Your Time
A few points to help you make the most of this book:
This book is designed as a visual introduction to neural networks. It is for BEGINNERS and those who have minimal knowledge of the topic. If you already have a general understanding, you might not get much out of this book.
You don’t need to read front to back. Skip around to what you find the most helpful or is perking your interest. We’ve included lots of links throughout the book to make this easy. Just click on them.
We *slowly* layer in new terminology and concepts each chapter. This means that if ............

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