Project overview
In this project, you’ll assume the role of a data scientist at a movie streaming company, tasked with developing a system that enables users to search for movies and get personalized recommendations to enhance user engagement.
Leveraging your Python skills and libraries like pandas and scikit-learn, you’ll work with movie data, build a search engine using TF-IDF and cosine similarity, and create a recommendation algorithm based on user ratings. The project will culminate in an interactive Jupyter widget showcasing the system’s capabilities, allowing users to input a movie and receive instant recommendations.
This hands-on project provides an opportunity to apply your data science skills to a real-world problem. You’ll gain practical experience in data manipulation, natural language processing, machine learning, and interactive widget development. The final product will be a valuable addition to your portfolio, demonstrating your ability to create intelligent systems that deliver user value.
Objective: Apply data science techniques using Python to build a movie search and recommendation system that enhances user experience and engagement on a streaming platform.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Working with Python data types, variables, functions, and control flow
- Exploring and preparing data using pandas DataFrames
- Using regular expressions to clean text data in Python
- Working in Jupyter Notebooks to write and run Python code
Projects steps
Step 1: Introduction
Step 2: Reading in Our Movie Data in Pandas
Step 3: Cleaning Movie Titles Using Regex
Step 4: Creating a TFIDF Matrix
Step 5: Creating a Search Function
Step 6: Building an Interactive Search Box in Jupyter
Step 7: Reading in Movie Ratings Data
Step 8: Finding Users Who Liked the Same Movie
Step 9: Determining How Much Users Like Movies
Step 10: Creating a Recommendation Score
Step 11: Building a Recommendation Function
Step 12: Create an Interactive Recommendation Widget
Step 13: Next Steps
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