Thursday, October 1, 2020

Pre-orders are Now Open for Deep Learning on Windows

Pre-orders for my new book, Deep Learning on Windows, are Now Open at!

Deep Learning on Windows is my latest book, and it is the longest and the most comprehensive book I have written to date. The book is meant for both beginners and intermediates to deep learning. It covers topics from setting up your tools on Windows and getting started, to complex but fun topics in deep learning and computer vision.

The Cover of 'Deep Learning on Windows'
The Cover of 'Deep Learning on Windows'

The Windows OS accounts for over 70% of the desktop PC usage. Windows provides many conveniences, with a wide variety of available productivity tools, causing it to gather a large userbase. This means that there is a large percentage of you - AI enthusiasts and developers - out there that primarily work on the Windows OS, and would prefer to develop deep learning models on Windows itself.

Deep Learning on Windows is meant to help you learn to build deep learning and computer vision systems, right within the familiar elements of Microsoft Windows. The goal of this book is to get as many of you interested in the field of Deep Learning and have the OS you build upon a non-barrier to start learning.

With this book, you will,
  • Learn the concepts, history, and milestones behind Deep Learning and how it relates to Machine Learning and AI while resolving some misconceptions surrounding those AI concepts.
  • Learn the tools you would require (TensorFlow, Keras, OpenCV, CUDA, etc.) to successfully learn building deep learning systems, and learn how to set up, configure, and troubleshoot them step-by-step. Learn to get the tools working on Microsoft Windows and learn why the OS or the hardware you are developing on does not hold you back in building state-of-the-art AI systems. Subsequently, this would allow you to break any mental barriers and allow applying what they have learned on any OS or any system.
  • Learn to build your first ‘hello world’ deep learning model and understand how the concepts of each step of it work through code examples. Learn how to visualize the internal workings and the structure of a model to gain a deeper understanding of how they work and allow you to apply that experience to develop more complex models in the future.
  • Learn to build real-world, practical deep learning computer vision systems with limited amounts of data with the concepts of transfer learning and fine-tuning. Learn how to configure training of larger models with large datasets and ways you can deploy your application once trained.
  • Once you have mastered the basics, learn more exciting and advanced concepts such as Generative Adversarial Networks, and Reinforcement Learning (for basics in game programming) that you can practically learn through examples.

The book will be released in December 2020. But you can pre-order you copy right now from Amazon via the following link,

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