A Mathematical Introduction to Data Science

This textbook provides a comprehensive foundation in the mathematics needed for data science for students and self-learners with a basic mathematical background who are interested in the principles behind computational algorithms in data science. It covers sets, functions, linear algebra, and calcul...

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Bibliografische gegevens
Hoofdauteurs:	Sun, Yi (Auteur), Adams, Rod (Auteur)
Coauteur:	SpringerLink (Online service)
Formaat:	Elektronisch E-boek
Taal:	Engels
Gepubliceerd in:	Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Editie:	1st ed. 2025.
Onderwerpen:	Artificial intelligence > Data processing. Computer science > Mathematics. Machine learning. Mathematical statistics. Artificial intelligence. Data Science. Mathematics of Computing. Machine Learning. Probability and Statistics in Computer Science. Artificial Intelligence.
Online toegang:	https://doi.org/10.1007/978-981-96-5639-4
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Inhoudsopgave:

Chapter 1 Introduction
Chapter 2 Sets and Functions
Chapter 3 Liner Algebra
Chapter 4 Matrix Decomposition
Chapter 5 Calculus
Chapter 6 Advanced Calculus
Chapter 7 Algorithms 1 – Principal Component Analysis
Chapter 8 Algorithms 2 – Liner Regression
Chapter 9 Algorithms 3 – Neural Networks
Chapter 10 Probability
Chapter 11 Further Probability
Chapter 12 Elements of Statistics
Chapter 13 Algorithms 4 – Maximum Likelihood Estimation and its Application to Regression
Chapter 14 Data Modelling in Practice.

A Mathematical Introduction to Data Science

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