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LEARN.md

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+# Learning Resources
+
+Welcome to our learning resources for building a Netflix recommendation system using Node.js, Express, and a recommendation engine using Python! Below, you'll find a curated list of resources to help you understand the concepts and technologies involved in this project.
+
+## Node.js and Express
+
+- [Node.js Documentation](https://nodejs.org/en/docs/): Official documentation for Node.js.
+- [Express.js Documentation](https://expressjs.com/): Official documentation for Express.js.
+- [Node.js Design Patterns](https://www.amazon.com/Node-js-Design-Patterns-Mario-Casciaro/dp/1783287314): Book on design patterns in Node.js by Mario Casciaro.
+
+## Netflix Recommendation System
+
+- [Netflix Recommendation System: Algorithms Behind the Curtain](https://medium.com/@NetflixTechBlog/netflix-recommendations-beyond-the-5-stars-part-1-55838468f429): Blog post series by Netflix Tech Blog on recommendation algorithms.
+- [Building a Netflix-style Recommender System in Python](https://towardsdatascience.com/building-a-netflix-style-recommender-system-in-python-e9bfc05a949b): Tutorial on building a recommendation system in Python.
+- [The Netflix Recommender System: Algorithms, Business Value, and Innovation](https://www.cs.cmu.edu/~wcohen/10-605/Netflix.pdf): Research paper on the Netflix recommendation system by Yehuda Koren et al.
+
+## Python Recommendation Engines
+
+- [Surprise Library Documentation](https://surprise.readthedocs.io/en/stable/index.html): Documentation for the Surprise library, a Python scikit for building and analyzing recommender systems.
+- [Building Recommendation Systems in Python](https://www.amazon.com/Building-Recommender-Systems-Python-supervised/dp/1789131389): Book on building recommendation systems in Python by Frank Kane.
+- [Hands-On Recommendation Systems with Python](https://www.packtpub.com/product/hands-on-recommendation-systems-with-python/9781788993753): Book on hands-on recommendation systems with Python by Rounak Banik.
+
+## Additional Resources
+
+- [Machine Learning Crash Course](https://developers.google.com/machine-learning/crash-course): Google's crash course on machine learning.
+- [Kaggle](https://www.kaggle.com/): Platform for data science competitions and datasets.
+- [Scikit-learn Documentation](https://scikit-learn.org/stable/): Documentation for the scikit-learn library for machine learning in Python.
+
+Happy learning and happy coding! If you have any questions or need further assistance, feel free to reach out to us.