11.7 - Building a Simple Recommender in Python (Collaborative Filtering)
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Practice Questions
Test your understanding with targeted questions
What does SVD stand for?
💡 Hint: Think about matrix decomposition and factorization in linear algebra.
What library do we use to build recommender systems in Python?
💡 Hint: It has 'surprise' in its name.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What percentage of the dataset is typically used for training?
💡 Hint: Think about common practices in data science.
True or False: RMSE can be used to measure the accuracy of predictions.
💡 Hint: Consider the definition of RMSE.
1 more question available
Challenge Problems
Push your limits with advanced challenges
You have a movie dataset. Propose how you would structure your recommendation system using collaborative filtering.
💡 Hint: Think about data attributes, algorithm choices, and user patterns.
Create a Python function that takes the user-item matrix, applies SVD, and returns the predicted ratings.
💡 Hint: Focus on the dataset initialization and model fitting process.
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