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Updated by kanger.dev on Feb 05, 2022
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Maths for Machine Learning, Deep Learning and AI

Maths is not an option for Machine Learning, Deep Learning and AI.

It is important to have thorough mathematical understanding.

So, we have compiled this list to help learners find the best Courses to learn gain the Mathematical intuition needed for Machine Learning and Ai.

These courses are suitable for absolute beginners to master the mathematical foundation required for writing programs and algorithms for Machine Learning, Deep Learning and AI.

Source: https://kanger.dev/mathematics-for-machine-learning-deep-learning-ai

Mathematics for Machine Learning: Linear Algebra

This Beginner-Level courses aims to equip learners with solid Math skills for Machine Learning to work with Eigenvalues And Eigenvectors, Basis (Linear Algebra), Transformation and Matrix Linear Algebra.

Mathematical Foundation For Machine Learning and AI

This Intermediate-Level course is suitable for learners with the basic knowledge of Python or R.

You will learn the key concepts for solving real world problems with Maths for Machine Learning.

Vector Calculus for Engineers

This Intermediate-Level course in Mathematics for Machine Learning will help you to learn scalar, vector fields, differentiating fields and integrating fields, including but not limited to theorems.

Mathematics for Machine Learning: Multivariate Calculus

This interactive course is for intermediate learners to you gain knowledge and skills in multivariate calculus and process of building the common machine learning techniques.

Mathematics for Machine Learning Specialization

This beginner-level Specialization is perfect for learners to gain the prerequisite mathematical knowledge, related to Data Science, Machine Learning and Deep Learning.

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