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### How we can start career with Machine Learning

- Linear algebra
- Probability theory
- Optimization
- Calculus
- Information theory and decision theory

- Python: Best for both beginner and advanced level.
- R: Good but slow run time.
- Matlab: Good but costly and slow.
- Julia: Very fast, good and limited libraries, as it is new.
- C++: Difficult, very fast and used in production.
- Recommend beginners to start with Python and learn only the required math from book and online courses. Some good books in Machine Learning and Deep Learning.

- For probability and statistics: Book by Stark and Woods 'Probability and Random Processes with Applications to Signal Processing'.
- For information theory: Book by Thomas and Cover 'Elements of Information Theory'.
- For linear algebra, apart from many great books such as 'Matrix Analysis' by 'Horn and Johnson', I would also recommend Gilbert Strang's video lectures on linear algebra (courtesy of OCW-MIT).