math-tutorials

This is a collection of tutorials that cover the fields of math commonly used in machine learning and is inspired by my studies in the International University of Applied Sciences, Berlin. Work in progress

1. Notes on HELM project:

   • HELM Workbook 1: Basic Algebra
   • HEML Workbook 2: Basic Functions
   • HELM Workbook 3: Equations, Inequalities, Partial Fractions

2. Probability and Statistics Tutorial:

   • Chapter 1:
     • Overview
     • The Importance of Probability and Statistics in ML
   • Chapter 2:
     • Getting Good with the Terms
       • Events, Random Variables, Sample Spaces, Probability

3. Mathematical Analysis:

   • Intro:
   • Chapter 1: Sequences and Series
   • Chapter 2: Functions and Inverse Functions
   • Chapter 3: Differential Calculus
   • Chapter 4: Integral Calculus
   • Chapter 5: Differential Equations

4. Algorithms and Data Structures:

   • Intro: