![]() Have extensive knowledge and understanding of a wide range of ML algorithms to be able to apply the correct the algorithm for the problem at hand.Have enough mathematical proficiency to be able to read academic papers or graduate level textbooks about ML.Applied Data Science II: Machine Learning & Statistical Analysis Applied Data Science I: Scientific Computing & Python Keith Galli - Complete Python NumPy Tutorialĭata science handbook (a bit verbose for self study) Programming: Corey Schafer – Python Programming Beginner TutorialsĬorey Schafer – Python OOP Tutorials – Working with ClassesĬorey Schafer – Jupyter Notebook Tutorial Khan Academy – Statistics and ProbabilityĬoncrete ML Knowledge: coursera – machine learningĬoursera – deep learning specialization (courses 1 to 4 on youtube)ĭmitry Kobak – introduction to machine learning 3blue1brown – Essence of linear algebra ![]() Gilbert Strang – MIT online lecture (find problems and solutions)
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