Mathematics for Machine Learning and Deep Learning

Description:

This tutorial provides an overview of Mathematics in Machine Learning and Deep Learning, including step-by-step explanations and examples of math problems in these fields. Its aim is to enhance your understanding of mathematics in relation to machine learning and deep learning education. 🔣 🔢

Prerequisites:

Python 3.0 +
Use jupyter notebook

List of Mathematics:

Basic Mathemathics

• Addition, Subtraction, Multiplication, Division, Square Root, and Algebra.

Geometry

• Shapes, Area, Perimeter, Volume, Points, Lines, Angles, Surfaces, Planes, and Curves

Statistics

• Data collection, Data Analysis, Probability, Average, Median, Mode, Standard Deviation, and Variances

Calculus

• Instantaneous rates of change and Slopes of curves, Differential, Integral, Series, Vector, and Multivariable

Linear Algebra

• Matrices, Vector Spaces, Linear Systems, Gaussian elimination, Linear Systems, Determinant, Eigenvalues and eigenvectors

Author:

• Tin Hang