In Building Recommendation Systems with Python training course you will learn the different kinds of recommenders used in the industry and how to build them from scratch using Python. No need to wade through tons of machine learning theory, you will get started with building and learning about recommenders quickly. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content-based and collaborative filtering techniques.
By attending Building Recommendation Systems with Python workshop, delegates will learn to:
- Understand the different kinds of recommender systems
- Master data-wrangling techniques using the pandas library
- Building an IMDB Top 250 Clone
- Build a content-based engine to recommend movies based on real movie metadata
- Employ data-mining techniques used in building recommenders
- Build industry-standard collaborative filters using powerful algorithms
- Building Hybrid Recommenders that incorporate content based and collaborative filtering
- Basic to Intermediate IT skills
- Basic Python syntax skills are recommended
- Good foundational mathematics or logic skills
- Basic Linux skills
- Developers, Analysts, and other professionals interested in learning the tools and techniques needed to build recommendation systems.