The Ultimate Beginners Guide to Python Recommender Systems

The Ultimate Beginners Guide to Python Recommender Systems, available at $59.99, has an average rating of 4.64, with 30 lectures, based on 165 reviews, and has 13828 subscribers.

You will learn about Understand the basics about recommender systems Understand the theory and mathematical calculations of collaborative filtering Implement user-based collaborative filtering and item-based collaborative filtering step by step in Python Use the following libraries for recommender systems: LibRecommender and Surprise Use the MovieLens dataset to generate movie recommendations for users This course is ideal for individuals who are People interested in recommender systems or Students who are studying subjects related to Artificial Intelligence or Data Scientists who want to increase their knowledge in recommender systems or Professionals interested in developing recommender systems or Beginners who are starting to learn recommender systems It is particularly useful for People interested in recommender systems or Students who are studying subjects related to Artificial Intelligence or Data Scientists who want to increase their knowledge in recommender systems or Professionals interested in developing recommender systems or Beginners who are starting to learn recommender systems.

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Summary

Title: The Ultimate Beginners Guide to Python Recommender Systems

Price: $59.99

Average Rating: 4.64

Number of Lectures: 30

Number of Published Lectures: 30

Number of Curriculum Items: 30

Number of Published Curriculum Objects: 30

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

• Understand the basics about recommender systems
• Understand the theory and mathematical calculations of collaborative filtering
• Implement user-based collaborative filtering and item-based collaborative filtering step by step in Python
• Use the following libraries for recommender systems: LibRecommender and Surprise
• Use the MovieLens dataset to generate movie recommendations for users

Who Should Attend

• People interested in recommender systems
• Students who are studying subjects related to Artificial Intelligence
• Data Scientists who want to increase their knowledge in recommender systems
• Professionals interested in developing recommender systems
• Beginners who are starting to learn recommender systems

Target Audiences

• People interested in recommender systems
• Students who are studying subjects related to Artificial Intelligence
• Data Scientists who want to increase their knowledge in recommender systems
• Professionals interested in developing recommender systems
• Beginners who are starting to learn recommender systems