Coding the Deep Learning Revolution


Get up to speed with Deep Learning using Python, Keras and TensorFlow 2!


Deep learning is the machine learning method that is producing state-of-the-art breakthroughs in fields such as:

  • Advanced object detection and tracking (also in autonomous driving systems!)
  • Neural machine translation approaching human levels of language translation
  • The ability to produce convincing synthetic human faces and other images
  • Automatic image and video captioning
  • Improved medical diagnostics
  • Stock market forecasting and automated trading systems
  • and so much more


If you’re anything like me, you enjoy learning new things. That’s good, because deep learning is a constantly evolving field of research, with new algorithms and methods to try out all the time.

Do you know what else is great about deep learning? It’s not that difficult to understand! Now, don’t get me wrong, you will have to work to gain an understanding of some fundamental concepts. You’ll also need to be willing to experiment a lot and develop a sense of curiosity.

But you don’t have to have a PhD in Mathematics! That’s good news.


In my book Coding the Deep Learning Revolution, you’ll learn about:

– What is deep learning and what’s its history?

– Computational graphs

– Weight initialization and why it’s important

– Vanishing gradients and their solution

– Convolutional neural network structures

– Recurrent neural network structures

– Drop-out, batch normalization and regularization

– Transfer learning

– and more…


In Coding the Deep Learning Revolution, you’ll learn all the theory, but in a beginner-friendly, maths-lite way. Each chapter also contains in-depth, step-by-step code walkthroughs to demonstrate how to apply the theory in Python, Keras and TensorFlow 2. TensorFlow 2 (with its Keras API) is the cutting edge of deep learning coding libraries, which meshes perfectly with Python.

In this book, I have relied on my experience of using machine and deep learning systems in my day-to-day work in a major utility company, my teaching experience from being a lecturer at a prestigious Australian university, and mentoring graduate and early-career engineers.

Here’s what you’ll get for $19.99:

  1.  CODING THE DEEP LEARNING REVOLUTION eBOOK: this 160 A4 page eBook covers all the key concepts mentioned above to get you up to speed in deep learning: Deep learning and its history, the computational graph, introductions to TensorFlow and Keras, weight initialization and activations, the vanishing gradient problem, Convolutional Neural Networks, Recurrent Neural Networks, Transfer Learning and more. Includes a multitude of worked code examples. All content is up-to-date for TensorFlow 2!
  2.  AN INTRODUCTION TO NEURAL NETWORKS FOR BEGINNERS eBOOK: This 40 A4 page eBook introduces the reader to all the major neural network concepts, such as activation functions, structure, hidden layers, gradient descent optimization, and regularization. Includes many worked code examples. This will get the reader up to speed and ready for deep learning.
  3.  ALL THE CODE: All the code is supplied free of charge to the reader, so you can run, step-through, manipulate and use yourself to enhance learning outcomes.
  4.  LIFETIME FREE UPDATES: The TensorFlow and Keras deep learning frameworks are in constant open source development. To stay relevant, this book will be updated whenever major changes to these frameworks occur.
  5.  7 DAY REFUND: Find that the book isn’t for you? No problem, ask for a refund within 7 days and I will give you back your money, no questions asked.

As stated above, you can purchase this book with no risk, given the 7-day money-back guarantee.

Here are some testimonies of my machine learning teaching style:

This is the best self-learning site I have ever come across for deep learning

Prashant Brahmbhatt


This tutorial is so much better for beginners, it actually explains what’s going on and what you are doing in every step. Now everything is way clearer

Luis Jalabert


Well done, this is outstanding work, many thanks for this article! Your tutorials are easy to follow and one can get familiar with the topic in an enjoyable way

Dirk Gooris

Good luck with your deep learning journey!