Building Recommendation Systems with Python - Udemy

Recommendation Engines have become an integral part of any application. For accurate recommendations, you require user information. The more data you feed to your engine, the more output it can generate – for example, a movie recommendation based on its rating, a YouTube video recommendation to a viewer, or recommending a product to a shopper online.

In this practical course, you will be building three powerful real-world recommendation engines using three different filtering techniques. You'll start by creating usable data from your data source and implementing the best data filtering techniques for recommendations. Then you will use Machine Learning techniques to create your own algorithm, which will predict and recommend accurate data.

By the end of the course, you'll be able to build effective online recommendation engines with Machine Learning and Python – on your own.

About the Author

Eric Rodríguez is a mechatronics engineer with an interest in the areas of machine learning and robotics. His passion for programming began around 5 years ago when he started learning how to build web applications. He moved on to develop Android applications and finally completed his Master's degree in Computer Science. He has also started using C# in Xamarin to develop mobile applications. Eric has years of practical experience in the software development industry as a software engineer.