The following math concepts are used in Machine Learning and every Machine Learning Professional must learn:
Linear Algebra
Topics to be covered:
- Principal Component Analysis (PCA)
- Singular Value Decomposition (SVD)
- Eigen decomposition of a matrix
- LU Decomposition
- QR Decomposition/Factorization,
Probability Theory and Statistics
Topics to be covered:
- Bayes’ Theorem,
- Random Variables
- Variance and Expectation
- Probability Distributions
- Maximum Likelihood Estimation (MLE)
- Sampling Methods.
You can sign up for this Machine Learning Course by Intellipaat to learn Machine Learning.
Also, watch this video on Mathematics for Machine Learning:
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