Recommender Systems with Machine Learning
Build Recommender Systems for Real-World Applications Using Machine Learning
Discover how to design and build effective recommender systems using machine learning. Gain practical experience by creating your own recommendation engines with Python, working on real-world datasets and hands-on projects. Develop a strong understanding of both the theory and application of these systems.
Packt | Mar 2023 | 377 min
What You Will Learn
You will start by exploring the core concepts and taxonomies behind recommender systems before moving into hands-on coding exercises. Through live coding sessions and two detailed projects, you will build and refine recommendation engines from scratch. Quizzes and practical tasks help reinforce your understanding as you progress.
Key Features
- Develop content-based and collaborative filtering models for personalized recommendations
- Apply machine learning techniques to real-world datasets using Python
- Evaluate and improve recommender system performance with practical methods
Target Audience
If you have basic Python skills and want to learn how to build your own recommender systems, this course is for you. It's ideal for aspiring data scientists, developers, or anyone interested in applying machine learning to real-world problems. No prior experience with machine learning or data analysis is required-just curiosity and a willingness to learn.
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