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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. :symbols: :1234:
<img src="Title_Math.PNG">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
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Author:
- Tin Hang