Mathematics for Machine Learning


Mathematics is an essential part for machine learning  without maths it is hard to get into core

concepts. In addition, machine learning uses concepts from different branches, however, these branch of mathematics are the backbone of the machine learning.

1- Linear Algebra

Matrix, Vector Spaces, Linear Transformations, Eigen Values and Eigen Vectors ( Principle Component Analysis)

2- Multivariate Calculas

Partial Differential Equations ( Support Vector Machines)

3- Probability and Statistics

Mean (K-Means Clusterning), Variance and Covariance ( Feature Reduction), Probability Distributions(  Classifiers), Bay’s Theorem ( Naiv Bayes Classifier)

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