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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