Building Recommendation Systems with Python [Video]

Building Recommendation Systems with Python [Video]

English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 35m | 358 MB
eLearning | Skill level: All Levels

Building Recommendation Systems with Python [Video]: Build real-world recommendation systems using collaborative, content-based, and hybrid filtering techniques in Python

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.