Maths for Machine Learning

1Essential Mathematics for Machine...
2Statistics and Probability 
3Linear Algebra for Machine Learni...
4Probability Distribution Definition
5Hypothesis Testing
6Maths for Machine Learning: Appli...

1. Essential Mathematics for Machine Learning - Introduction

Machine Learning can be defined as a field that correlates the statistical, probabilistic, computer science and algorithmic aspects arising from learning iteratively from the data and finding hidden insights which might be useful to build intelligent applications. Despite the huge prospects of Machine Learning, an intensive mathematical understanding of these techniques is required to grasp the inner workings of the algorithms and obtaining good results.

Why take stress about Mathematics

Basic Mathematics is ought to have an in-depth understanding of machine learning concepts, furthermore as to:

  1. Finding out an optimum algorithm for a specific case
  2. To grab the in-depth concepts of Machine Learning
  3. Identifying underfitting and overfitting


  • Probability and Statistics
  • Linear Algebra
  • Probability Distribution
  • Hypothesis testing
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