What will you get from this book?


infographic9Product recommendation

Learn Amazon's recommendation technique and enhance your sales.

mix02 - CopyMachine Learning

Learn a new Machine Learning or Data Scientist skill and boost your Resume.

05 - CopyMovie recommendation

Show the appropriate video to people visiting your website and hook them.

13505-NOZZJV - CopyNews recommendation

Learn which news or blog post to display to your website's visitors.

previewFriend recommendation

Understand Facebook and LinkedIn's user-to-user recommendation system.

05 - CopyAppropriate Recommender

Learn how to choose the best technique for a certain recommendation task.


What others say?



 "Fantastic book. It provides great examples of real solutions used by known companies such as Amazon, Facebook, etc. and subsequently explains them. This ebook is a tome of information on Machine Learning and Recommender Systems."

-Karl Adams, Machine Learning Engineer


"I maintain an e-commerce website for selling books. Over the past few months, I have been struggling on suggesting good books to my existing and new customers. The writer shows state-of-the-art recommendation techniques and explains how to design them. This was a very informative book and I will be trying to build a recommender system for my website based on the things I learned from this book."

-Christopher Weill, Owner of multiple localized e-commerce sites


An absolute must-have for Tech Entrepreneurs and Machine Learning enthusiasts.


My goal is to give you (and the 2,500+ other people who have downloaded this FREE ebook) an opportunity to learn the technology behind the recommendations you receive every day from social media, movie streaming sites and e-commerce stores.

I know that learning mathematical techniques can be very intimidating. Hence, I have explained the complex concepts of Machine Learning in simple terms with lots of illustrative examples. Implement one or more of the techniques that are shown in this book in your favourite tool and see their true potential.


2500+ happy readers! Take action and read this book. In no time, you will start using Machine Learning to build Recommender Systems.