A minimal study plan for Machine Learning 📈

Python:

• freeCodeCamp: https://t.co/jS6WKmMtIt

• CS50p Harvard: https://cs50.harvard.edu/python/2022/

• Corey Schafer: https://t.co/zORb4tbfHc (refer as you need)

Maths for ML:

• Khan Academy: https://t.co/BkGP6UC8eM

• Maths for ML Imperial College: https://t.co/M3iTPec0WT

• Seeing Theory Brown University: https://seeing-theory.brown.edu/

Machine Learning:

• Andrew Ng Coursera: https://t.co/yEi82fj9Yk

• ISL Book: https://www.statlearning.com/

• Deep Learning Coursera: https://t.co/OW4jAkuqTP

MLOps:

• MLOps Specialization Coursera: https://t.co/g8ayWl8u8i

• Made with ML: https://madewithml.com/

Practice:

• Kaggle: https://www.kaggle.com/

LLMs:

• LightningAI Blogs: https://lightning.ai/pages/community/

• LangChian & VectoDBs: https://learn.activeloop.ai/courses/langchain?ref=bd932c