Welcome to "AI/ML Unlocked", an interactive workshop hosted by Naman Vrati, GDG Campus AI/ML Lead! 🚀 This beginner-to-intermediate level session introduces Traditional AI concepts and ends with a hands-on case study: building a Netflix-style recommendation engine in Python using Pandas and Cosine Similarity.
🔍 Ever wondered how Netflix knows what to recommend next, or how ChatGPT sounds smarter than WhatsApp replies? Let's decode AI magic behind the scenes!
- What is AI? Traditional AI vs. Generative AI
- Real-world use cases of AI (Netflix, Spotify, ChatGPT)
- Fundamentals of recommendation systems
- Cosine Similarity for content-based filtering
- Hands-on coding in Google Colab
- Building your first Netflix Movie Recommender!
- 🐍 Python 3.x
- 📊 Pandas
- 🔬 Scikit-learn
- 🔗 Cosine Similarity
- 🧠 Google Colab
We use a cleaned and pre-processed version of a Netflix movies dataset.
You don’t need to install anything locally! Everything runs in the browser via Google Colab. Follow these steps:
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Click below to open the notebook:
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Run the code blocks sequentially
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Experiment with your own movie names 🎥
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Share your results and tag me on LinkedIn!
| 🔗 Google Colab | 🐙 GitHub Repo | 📝 Feedback Form | ||||
|---|---|---|---|---|---|---|
If you enjoyed this, feel free to:
- ⭐ Star the repo
- 🧠 Fork and play with the notebook
- 📸 Share your output & tag me!
🔗 LinkedIn: Naman Vrati
🐙 GitHub: NamVr
📧 Email: info@namanvrati.me
