Build Your Own Neural Network in Python
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Build Your Own Neural Network in Python

About the Book

What's the first thing that comes to your mind when you think of machine learning?

And you start thinking, I need a PhD in 10 different disciplines just to get started with this! 

But what if machine learning wasn't so hard? What if you could build your own Neural Network from scratch, using basic Python?

Introducing Neural Networks

Neural Networks are machine learning algorithms loosely modeled on the human brain. They are great at solving complex problems like image recognition and speech processing.

Even though Neural Networks can solve complex problems, their implementation is fairly easy, and only uses high school level maths (and if even that scares you, I will cover all the maths required with examples).

To reiterate: We will be using very little maths. The focus will be on practical stuff.

What we will go over in this eBook:

1. Theory behind Neural Networks

2. A simplified intro to the maths behind neural networks

3. Back propagation, multiple layers and more

4. A complex example, like recognise handwritten digits

Bonus

  • Introduction to Keras
  • Carry out Sentiment analysis on movie reviews
  • Build your own image detector, recognise images like cars, ships and different animals etc

About the Author

Shantnu Tiwari
Shantnu Tiwari

Shantnu trained as an Electronics Engineer, and spent several years working with low level code, including DSPs,  embedded systems and embedded Linux.

  Soon, he grew disillusioned by fixing dangling pointers, memory leaks, race conditions, bugs which only appeared once every two weeks.

In desperation, Shantnu threw up his hands and said, “Lord! Is there more than life to this?”

And that night, SpongBob SquarePants appeared in his dream. “My son,” he said, “try Python. It will fix all your problems.”

And Shantnu did, and lo! All was well.

And now, Shantnu is sharing the love…

Table of Contents

  •  
    • Introduction
    • Human Brains vs Computers
      • Neurons and Artifical Neuron Networks
  • Building Our Neural Network: Learning the Basics
    • More on Neurons
      • A Very Basic Neural Network
    • A Fully Worked Example
    • Matrix Multiplication
    • Back Propagation and Hidden Layers
      • Back Propagation
      • Error updating with Matrixes
    • Updating the Weights
  • Coding Our Neural Network
    • Preparing the Input and Weights
    • Reading Handwritten Digits
    • Chapter 9: Build Our Neural Network
      • Step 1: Initialize our weights
    • Predict Handwritten Digits
      • Testing the neural network
    • Using Your Own Handwriting Sample
  • Case Studies and More Examples
    • Keras: High Level Interface to NN
    • Use Keras to Detect and Identify Thousands of Image Types
  • Bye Byes are Sad
  • APPENDIX
    • Machine Learning For Complete Beginners
      • Introduction to Machine Learning
      • Machine Learning with Python
      • Why Programming Practice is Needed
      • Titanic Practice Sessions

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