Linear Algebra 🧮Įssence of linear algebra by 3Blue1Brown A geometric understanding of matrices, determinants, eigen-stuffs and more. This course is of intermediate difficulty and will require basic Python and numpy knowledge.Īt the end of this specialization you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning. The third course, Dimensionality Reduction with Principal Component Analysis, uses the mathematics from the first two courses to compress high-dimensional data.
It starts from introductory calculus and then uses the matrices and vectors from the first course to look at data fitting. The second course, Multivariate Calculus, builds on this to look at how to optimize fitting functions to get good fits to data. Then we look through what vectors and matrices are and how to work with them. In the first course on Linear Algebra we look at what linear algebra is and how it relates to data. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science. Mathematics for Machine Learning Specialization by Imperial College London on Coursera In this video, I’ll describe my strategy to learn mathematics as fast as possible. How to Learn Mathematics Fast by Siraj Raval Whether you're interested in AI or you just want to do some real engineering work, you’re going to need to brush up on your math skills. The Mathematics of Machine Learning by MajorPrep The Map of Mathematics by MajorPrep The entire field of mathematics summarised in a single map! This shows how pure mathematics and applied mathematics relate to each other and all of the sub-topics they are made from. I have added links to MOOCs🎓, YouTube▶️ Playlists and Free e-books📚. Math is a specific, powerful vocabulary for ideas and giving a structure to the way you learn it will empower you to absorb much more of it much faster. It doesn’t matter what catches your fancy, machine learning, artificial intelligence, or deep learning you need to know the basics of math and stats-linear algebra, calculus, optimization, probability-to get ahead. In this post I have compiled great e-resources for learning Mathematics for Machine Learning.
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