Are you afraid that AI might take your job? 
Make sure you are the one who is building it.

  • Learn just enough math to be dangerous.
  • Get familiar with Python and TensorFlow.
  • Understand the main Deep Learning concepts.
  • Explore and implement 12 neural network architectures.
  • Solve various real-world problems with neural networks.
  • Learn how to generate images with neural networks.

Why should you learn Deep Learning?


Why should you invest in this book?

Not so long ago, Andrej Karpathy famously tweeted: “Gradient descent can write code better than you. I’m sorry.” What he was trying to say is that neural networks, which use Gradient descent optimization technique, will soon be able not just to write code, but to write code better than us – software developers. This is how the story of “Software 2.0” paradigm begins. Basically, everything that we have been doing up until now can be considered “Software 1.0”. We explicitly write code to achieve some goal. In “Software 2.0”, we feed data to the algorithm and it does it on its own. Of course, we are not there yet, but….

I can remember that exact spark of jealousy and flush of FOMO that got me into the field of deep learning. It happened while I was first watching the video that combines Space Odyssey and Picasso’s painting style. Kubrick’s masterpiece mashed together with cubism. Brilliant! Amazing! Creative! That is what I wanted to do!

As it turned out, Deep Learning was not just another language or programming principle. I had to really buckle up. During this process I took notes, writing down my struggles. That is how Deep Learning for Programmers book was created. In this book, I’ve tried to explain the most important topics for deep learning and data science in general, using a software development perspective. Some of the concepts are implemented using the Object-Oriented approach just so the people with such knowledge can have a deeper understanding of the mentioned concepts. 

If you are a software developer and you want to learn deep learning, well this is the right book for you!

Nikola Živković has proven to be an expert on this topic. His pragmatic approach can be used by any software developer that is eager to understand what deep learning is all about. After reading this book, I don’t fear that I’m missing out. Professionals who read this book will quickly understand how to apply their existing codding skills on this subject.

Boban Miksin


What’s Inside


Mathematics for AI


Python Basics


Tensorflow 2.0 Guide


Neural Networks for Classification


Neural Networks for Regression


Convolutional Neural Networks


Recurrent Neural Networks






Self-Organizing Maps




Restricted Boltzmann Machine


Generative Adversarial Networks

Deep Learning for Programmes gently guides you through the world of neural networks. Starting from the most basic principles like basics of TensorFlow, to the more complex topics like GANs, it covers all niches. Once you finish this book you will have a clear picture of what you can do with this technology and how.

Petar Savic


There is More…

You don’t have to do everything on your own


Bonus #1

Transfer Learning 


Neural Networks can get huge. If you try to implement one of the state-of-the-art solutions, chances are that it would take a lot of time and resources to train these networks. TensorFlow has numerous pre-trained models that you can quickly utilize to build your specific solution. Little fine-tuning can get you far with these bad boys. Learn how to utilize these models for your specific problem.

This book is a pedagogical introduction to the concepts of deep learning that captures both the basics of machine learning as well as some very advanced topics, like transformers and GAN. Inspiring and encouraging voice of the author guides the reader from the underlying statistics and algebra basics to the cutting-edge applications and recent developments. Many interesting examples are illustrated with code and worked out in detail in a clear and friendly manner, which provides the aspiring data scientist or the AI researcher with all the necessary tools to dive into this wonderful and exciting subject in only 250 pages. I would recommend this book not only to the beginners, but also to the AI practitioners as an amazing overview of this conceptually rich and expanding field.

Luka Nenadovic

PhD. Theoretical Physicist and AI Researcher

Backbone of Object Oriented Programming


Bonus #2

SOLID Principles 


Learn how to write proper Object-Oriented code in Python. Writing clean code is one of the skills that can save you and your team a bunch of time. Avoid bugs, and start writing your code in an organized manner. SOLID principles are the first step towards this goal. Everything is, of course, done in Python.

If you are interested in machine learning and AI and you don’t know where to start, this book is what you need.
It has a clear explanation for all major neural network architectures, as well as the details how each of them functions. Code in the book is understandable and really well presented.
Apart from that, this book covers some topics, like Math and Python basics, which helped me tremendously to understand all that followed.
Big recommendation!

Marinko Spasojević

CTO and Author

A picture is worth a thousand words


Bonus #3

Visualized Neural Networks Zoo


The world of neural networks is huge. It is easy to forget what certain architecture looks like and how it is working. That is why we prepared a visualized reminder for you. Here you can find all important networks visually presented, so you can print them out and use them during studying and development.

We Don’t do sales, but…

Given the circumstances and the severity of the situation, we decided to change that. We have got a number of emails from readers who want to use this isolation period to study Deep Learning rather than just spending time idly at their home.

However, don’t be fooled, this sale isn’t meant for profit and it’s most definitely not planned.  The rest of the year will be hard. This isolation period will pass, but the economy will take a huge hit. Some estimations say that we are facing crisis bigger than in 2008. Now, we are not writing this to scare you, but to emphasize that we need to be better than ever before and get the world back on track as soon as possible.

This sale is here to help people who want to become better, learn new skills and be more productive than ever before.

Live Long and Prosper,

Rubik’s Code Team

About the Author

Nikola Živković is a software developer with over 10 years of experience in the industry. He’s earned a Master’s degree in Computer Science from the University of Novi Sad in 2011, but by then he had already been working for several companies. During the time span in the industry, he has worked on large enterprise systems, as well as on small web projects. 

In the past couple of years he has been specializing in Data Science (Machine Learning and Deep Learning to be precise) and his goal is to unite this knowledge together with some best traditional programming practices. 

He is also experienced as a speaker and author, talking at meet-ups and conferences, and as a guest lecturer at the University of Novi Sad. You can find his online courses on Pack Publishing and Educative. 

More testimonials

This book is an excellent way to start learning Deep Learning, but it’s also a fruitful “tool ” for more experienced engineers who are already in Data Science/AI world.

Jovan Stojanovic


Deep Learning for Programmers is THE book for Deep Learning. Nikola succeeds to give you the essential theory behind mathematics, statistics, programming and then makes it even better with real-world examples in C# and Python. Nikola makes math, statistics and especially Deep learning great again, as they should be.

Manya Bogicevic


One of the most comprehensive book in the field of machine and deep learning on the market. All essentials from the math, statistics, programming, machine, and deep learning Nikola covered with such ease and professionalism. No matter if you have a technical or business background, you will definitely find it useful in your journey to becoming a top Data Scientist.

Nikola Basta

Machine Learning Engineer