Make your own Neural Network

Learn to Make your own neural network with this easy introduction to the mathematics and theory behind the most powerful Machine Learning technology!

The following is a review of the book Make Your Own Neural Network by Tariq Rashid. A wonderful journey where you will make your own Artificial Neural Network (ANN) and become familiar with the main concepts of this family of models.

Overview

Interested in Machine Learning or computer programming?

Want to learn how Artificial Neural Networks function and build one yourself?

Then we have the perfect book for you.

In ‘Make your own Neural Network‘, Tariq Rashid clearly and concisely explains how Artificial Neural Networks operate from all angles: the logic behind them, the mathematics and theory, and lastly the code and practical implementation.

‘Make your own Neural Network‘ is a perfect marriage of simplicity and exhaustive information about the subject, composing a text that is excellent for newbies to the field with no previous knowledge of neural networks or with rusty maths and also illuminating and delightful for those that are already familiar with the field.

Having said this, you will make the most out of if you feel reasonably confortable with simple maths, know your way around computers, and even have some programming experience.

It takes a learn first, build after approach, following a path that starts with learning the theory and laying the foundation of the maths behind Artificial Neural Networks (ANN) and then teaching us to implement one in a Raspberry Pi.

Lets see a breakdown of the content!

Content of Make your own Neural Network

The book is divided into three parts:

Part 1 is about ideas. It introduces the mathematical ideas underlying the neural networks gently with lots of illustrations and examples. The author presents the core concepts of a simple neural network with a highly engaging style, taking the reader through each decision and clearly explaining the mathematics required with great illustrations and acompaning text.

Part 2 is practical. Introduces the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. It delves into Python code to exercise the concepts and walks through the code in sufficient detail so that both novice and experienced coders can easily understand.

Part 3 extends these ideas further. This section pushes the performance of our neural network to an industry leading 98% using only simple ideas and code, tests the network on your own handwriting, guides us to taking a privileged peek inside the mysterious mind of a neural network, and even gets it all working on a Raspberry Pi.

As you can see, like we mentioned before Make your own neural network touches every topic you need to learn how ANNs work, implement them, and learn to optimise them and build real products.

With this great text you will build your own neural network from scratch and you will get an introduction to neural networks that is amongst the top in the market right now.

You can find the Github repo for the code here.

Summary of Make your own Neural Network

This book is a fun and relaxed journey through the main concepts of Artificial Neural Networks, starting from very simple ideas and gradually building an understanding of how neural networks work.

You don’t need any complex mathematics to understand the text, nor programming experience – you will learn to code in Python and make your own neural network from scratch.

You will learn how to create you own neural network while having fun and discovering a beautiful world. You can find this book on Amazon at the best price here:

For further resources on Artificial Neural Networks check out all this we have prepared for you:

• First we have three reviews of awesome but different Deep Learning books:
  • Deep Learning from Scratch – A book for people that already have a wide experience on the world of ANNs and that want to deepen their knowledge covering both theory and practice.
  • Deep Learning by Goodfellow et al – The most comprehensive and exhaustive book on the theory behind artificial neural networks, written by some of the most well known personalities on the field.
  • Grokking Deep Learning – A book similar to Make your own Neural Network, with great illustrations and explanations.
• Our awesome Machine Learning Tutorials category where you can find some awesome resources to keep learning about Neural Networks and Deep Learning.
• Neural Networks and Deep Learning by Michal Nielsen: a great online resource to learn Deep Learning.
  

As always, thanks a lot for reading How to Learn Machine Learning and have a great day!

About the author

Tariq Rashid has a degree in Physics, a Masters in Machine Learning and Data Mining, is active in London’s tech scene, leads the London Python meetup group (almost 3000 members) and loves doing talks/workshops whenever he can. For a day job, he works mostly in technology and digital strategy, but really he’s trying to introduce design thinking. He loves open source, and was lucky enough to lead on open source reform for the UK Government.

Tags: How to build your own neural network, Make your own neural network, How to Create your own neural network, Artificial Neural Networks, Deep Learning