Supervised Learning: Classification and Regression

Download: https://faculty.ucmerced.edu/mcarreira-perpinan/teaching/CSE176/lecturenotes.pdf

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💛 Top 10 Best Websites to Learn Machine Learning ⭐️
by [@codeprogrammer]

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🧠 Google’s ML Course
🔗 https://developers.google.com/machine-learning/crash-course

📈 Kaggle Courses
🔗 https://kaggle.com/learn

🧑‍🎓 Coursera – Andrew Ng’s ML Course
🔗 https://coursera.org/learn/machine-learning

⚡️ Fast.ai
🔗 https://fast.ai

🔧 Scikit-Learn Documentation
🔗 https://scikit-learn.org

📹 TensorFlow Tutorials
🔗 https://tensorflow.org/tutorials

🔥 PyTorch Tutorials
🔗 https://docs.pytorch.org/tutorials/

🏛️ MIT OpenCourseWare – Machine Learning
🔗 https://ocw.mit.edu/courses/6-867-machine-learning-fall-2006/

✍️ Towards Data Science (Blog)
🔗 https://towardsdatascience.com

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💡 Which one are you starting with? Drop a comment below! 👇
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This Machine Learning Cheat Sheet Saved Me Hours of Revision ⏳

It includes:
✅ Supervised & Unsupervised algorithms
✅ Regression, Classification & Clustering techniques
✅ PCA & Dimensionality Reduction
✅ Neural Networks, CNN, RNN & Transformers
✅ Assumptions, Pros/Cons & Real-world use cases

Whether you're:
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this one-page guide is a must-save.

♻️ Repost and share with your ML circle.

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