Do you want to learn how to write your own codes and programming and get your computer set up to learn just like humans do? Do you want to learn how to write out codes in deep learning-without having to spend years going to school to learn to code and how all this works? Do you know a bit of Python coding and want to learn more about how this deep learning works?

This guidebook is the tool that you need to not only learn how to do machine learning but also learn how to take this even further and write some of your own codes in deep learning. The field of deep learning is pretty new, and many programmers have not been able to delve into the depths of what we can see with this type of programming-but with the growing market for products and technology that can act and learn just like the human brain, this field is definitely taking off!

This book will take some time to explore the different Python libraries that will help you to do some deep learning algorithms in no time. Investing your time in the Python language and learning the different libraries that are needed to turn this basic programming language into a deep learning machine can be one of the best decisions for you.

By learning some of the tips in this book, you will be able to save time and resources when it comes to your deep learning needs. Rather than spending time with other, more difficult programming languages, or having to go take complicated classes to learn how to do these algorithms, we will explore exactly how to do all of the tasks that you need with this type of machine learning.

You will learn:

1. What deep learning is, how it is different from machine learning, and why Python is such a beneficial language to use with the deep learning algorithms;

2. The basics of the three main Python languages that will help you get the work done-including TensorFlow, Keras, and PyTorch;

3. How to install the three Python libraries to help you get started;

4. A closer look at neural networks, what they are, why they are important, and some of the mathematics of making them work;

5. The basics you need to know about TensorFlow and some of the deep learning you can do with this library;

6. The basics of the Keras library and some of the deep learning you can do with this library;

7. A look at the PyTorch library, how it is different from the other two, and the basics of deep learning with this library;

8. And so much more!

Even if you are just a beginner, with very little programming knowledge but lots of big dreams and even bigger ideas, this book is going to give you the tools that you need to start with deep learning!