Name: Basic Mathematics for Data Science with Python
Brand: LIBRAIRIE COREENNE
SKU: 154791
Price: 37.00 EUR
Availability: InStock

Basic Mathematics for Data Science with Python

€37,00

Basic Mathematics for Data Science with Python

Description

Book Introduction

Essential basic math for getting started with data science!

The synonym of the 4th Industrial Revolution is data science.
To understand data science, you must first understand mathematical concepts.
This book selects only the mathematics essential for studying data science.
It is structured so that you can learn along with Python coding.
This book will take you one step closer to data science.

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index

Chapter 1.
function
1.1 Function
1.2 Composite functions
1.3 Inverse function
Summary of programming functions
Practice problems
Programming practice

Chapter 2.
Various functions
2.1 Polynomial functions
2.2 Exponential and logarithmic functions
2.3 Trigonometric functions
Summary of programming functions
Practice problems
Programming practice

Chapter 3.
Extremes and Continuity
3.1 Sequences and recurrence relations
3.2 Limits of sequences
3.3 Limits of functions
3.4 Continuity of functions
Summary of Programming Functions
Practice problems
Programming practice

Chapter 4.
differential
4.1 Differentiation coefficients and derivatives
4.2 Differentiation
4.3 Higher-order derivatives
4.4 Differentiation of composite functions and inverse functions
4.5 Differentiation of implicit functions and parametric functions
4.6 L'Hopital's Rule
4.7 Applications of Differentiation
Summary of Programming Functions
Practice problems
Programming practice

Chapter 5.
integral
5.1 Indefinite integrals
5.2 Integration of various functions
5.3 Substitution integration method
5.4 Integration by parts
5.5 Definite integral
5.6 Applications of Integration
Summary of Programming Functions
Practice problems
Programming practice

Chapter 6.
Vectors and Space
6.1 Vectors
6.2 Spatial coordinates
6.3 Inner and outer products
6.4 Equations of lines and planes
Summary of Programming Functions
Practice problems
Programming practice

Chapter 7.
procession
7.1 Matrices and Basic Operations
7.2 Inverse matrix and determinant
7.3 Systems of linear equations
7.4 Gaussian elimination
7.5 Primary transformation
Summary of Programming Functions
Practice problems
Programming practice

Chapter 8.
Probability and Statistics
8.1 Permutations and Combinations
8.2 Binomial theorem
8.3 probability
8.4 Mean and standard deviation
8.5 Probability Distributions
8.6 Estimated
Summary of Programming Functions
Practice problems
Programming practice

supplement.
Standard normal distribution table