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Articles Home » Artificial Intelligence and Machine Learning » Become an AI and Machine Learning Specialist, Part I

Become an AI and Machine Learning Specialist, Part I

Building a Recommendation System with Python Machine Learning & AI with Lillian Pierson, P.E.

1h 38m • COURSE
Discover how to use Python—and some essential machine learning concepts—to build programs that can make recommendations. In this hands-on course, Lillian Pierson, P.E. covers the different types of recommendation systems out there, and shows how to build each one. She helps you learn the concepts behind how recommendation systems work by taking you through a series of examples and exercises. Once you're familiar with the underlying concepts, Lillian explains how to apply statistical and machine learning methods to construct your own recommenders. She demonstrates how to build a popularity-based recommender using the Pandas library, how to recommend similar items based on correlation, and how to deploy various machine learning algorithms to make recommendations. At the end of the course, she shows how to evaluate which recommender performed the best.
Topics include:
  • Working with recommendation systems
  • Evaluating similarity based on correlation
  • Building a popularity-based recommender
  • Classification-based recommendations
  • Making a collaborative filtering system
  • Content-based recommender systems
  • Evaluating recommenders


1. Introduction
01. Welcome
02. Using the exercise files



2.Simple Approaches to Recommendation Systems
03. Introducing core concepts of recommendation systems
04. Popularity-based recommenders
05. Evaluating similarity based on correlation



3. Machine Learning Recommendation Systems
06. Classification-based collaborative filtering
07. Model-based collaborative filtering systems
08. Content-based recommender systems
09. Evaluating recommendation systems



4. Conclusion
10. Next steps



· Posted by Superadmin on January 21 2019 · 0 Comments · 1263 Reads · Print
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