Books — statistics

EN
Statistics for Machine Learning

Statistics for Machine Learning

A

Pratap Dangeti

Algorithms and theory
EN
R Cookbook

R Cookbook

A

Paul Teetor

Programming languages
EN
Data Analysis and Graphics Using R – an Example-Based Approach, Third Edition

Data Analysis and Graphics Using R – an Example-Based Approach, Third Edition

A

John Maindonald, W. John Braun

AI and ML
EN
Data Analysis with Open Source Tools

Data Analysis with Open Source Tools

A

Philipp K. Janert

AI and ML
EN
Data Analysis Foundations with Python

Data Analysis Foundations with Python

A

Cuantum Technologies

AI and ML
EN
Exploring Everyday Things with R and Ruby

Exploring Everyday Things with R and Ruby

A

Sau Sheong Chang

AI and ML
EN
R for Stata Users

R for Stata Users

A

Robert A. Muenchen, Joseph M. Hilbe

Programming languages
EN
Essential Math for AI

Essential Math for AI

A

Hala Nelson

Algorithms and theory
EN
Foundations of Data Science with Python

Foundations of Data Science with Python

A

John M. Shea

Algorithms and theory
EN
Math for Deep Learning: What You Need to Know to Understand Neural Networks

Math for Deep Learning: What You Need to Know to Understand Neural Networks

A

Ronald T. Kneusel

AI and ML
EN
15 Math Concepts Every Data Scientist Should Know

15 Math Concepts Every Data Scientist Should Know

A

David Hoyle

AI and ML
EN
Data Science For Dummies

Data Science For Dummies

A

Lillian Pierson

AI and ML
EN
Data Science from Scratch: First Principles with Python, Second Edition

Data Science from Scratch: First Principles with Python, Second Edition

A

Joel Grus

AI and ML
RU
Joel Grus - Data Science from Scratch - 2017

Joel Grus - Data Science from Scratch - 2017

F
WEB development
EN
Data Science from Scratch

Data Science from Scratch

A

Joel Grus

AI and ML
EN
Bayesian Analysis with Python Third Edition: A practical guide to probabilistic modeling

Bayesian Analysis with Python Third Edition: A practical guide to probabilistic modeling

A

Osvaldo Martin

Algorithms and theory
RU
Fundamentals of Data Analysis in R

Fundamentals of Data Analysis in R

A

Никита Ткаченко

AI and ML
EN
Data Science For Dummies, 3rd Edition

Data Science For Dummies, 3rd Edition

A

Lillian Pierson

AI and ML
EN
Basic Math for AI: A Beginner’s Quickstart Guide to the Mathematical Foundations of Artificial Intelligence

Basic Math for AI: A Beginner’s Quickstart Guide to the Mathematical Foundations of Artificial Intelligence

A

Andrew Hinton

Algorithms and theory
RU
Wickham H. - Learning Shiny - 2022

Wickham H. - Learning Shiny - 2022

A

Х. Уикем

Programming languages
RU
Roig-Fusté J. M. - Python for Psychology, Social Sciences, and Education - 2026

Roig-Fusté J. M. - Python for Psychology, Social Sciences, and Education - 2026

A

J. M. Roig-Fusté

Programming languages
RU
Python for Data Analysis. Data Processing, Statistical Modeling, and Machine Learning

Python for Data Analysis. Data Processing, Statistical Modeling, and Machine Learning

B

Уэс Маккинни

AI and ML
RU
Learning Data Science. Data Processing, Exploration, Visualization, and Modeling with Python

Learning Data Science. Data Processing, Exploration, Visualization, and Modeling with Python

A

Сэм Лау, Джозеф Гонсалес, Дебора Нолан

Algorithms and theory
RU
Causal Analysis in Data Science

Causal Analysis in Data Science

A

Алекс Руис де Вилья Роберт

AI and ML
EN
Statistics with Rust: 50+ Statistical Techniques Put into Action

Statistics with Rust: 50+ Statistical Techniques Put into Action

A

Keiko Nakamura

Programming languages
EN
The Book of R: A First Course in Programming and Statistics, 2nd Edition

The Book of R: A First Course in Programming and Statistics, 2nd Edition

A

Tilman M. Davies

Programming languages
RU
Shipunov A.B., Baldin E.M., Volkova P.A., et al. Visual Statistics

Shipunov A.B., Baldin E.M., Volkova P.A., et al. Visual Statistics

A

А. Б. Шипунов, Е. М. Балдин, П. А. Волкова

Algorithms and theory
RU
Statistical Methods for Data Mining.PDF

Statistical Methods for Data Mining.PDF

F

Леонид Мыльников

Algorithms and theory
RU
Statistics and Experimental Design for the Uninitiated: How to Stop Statistics from Lying

Statistics and Experimental Design for the Uninitiated: How to Stop Statistics from Lying

A

Майкл Х. Херцог, Грегори Фрэнсис, Аарон Кларк

Algorithms and theory
RU
Statistics Without Tricks: Methods for Critical Data Analysis and Causal Inference

Statistics Without Tricks: Methods for Critical Data Analysis and Causal Inference

A

Итан Буэно де Мескита, Энтони Фаулер

Algorithms and theory
RU
Web Data Collection with R 2017 Khramov

Web Data Collection with R 2017 Khramov

F

Дмитрий Храмов

Programming languages
RU
Data Science Interview Preparation Guide

Data Science Interview Preparation Guide

A

Ренат Алимбеков

IT management
RU
Regression: Theory and Practice. With Examples in R and Stan

Regression: Theory and Practice. With Examples in R and Stan

A

Эндрю Гельман, Дженнифер Хилл, Аки Вехтари

Programming languages
RU
Mathematics for Data Science. Managing Data with Linear Algebra, Probability Theory, and Statistics

Mathematics for Data Science. Managing Data with Linear Algebra, Probability Theory, and Statistics

A

Томас Нилд

Algorithms and theory
RU
Data Science: A Learning Course

Data Science: A Learning Course

A

Стивен С. Скиена

AI and ML
RU
Visual Statistics. Using R!

Visual Statistics. Using R!

A

А. Б. Шипунов, Е. М. Балдин, П. А. Волкова, А. И. Коробейников, С. А. Назарова, С. В. Петров, В. Г. Суфиянов

AI and ML
RU
Diving into Data Analytics

Diving into Data Analytics

A

Джордж Маунт

AI and ML
RU
Mathematical Packages: R

Mathematical Packages: R

D

В. А. Шишкин

Algorithms and theory
RU
Cook D. Machine Learning with

Cook D. Machine Learning with

F

Д. Кук

AI and ML
RU
How Not to Be Wrong: The Power of Mathematical Thinking

How Not to Be Wrong: The Power of Mathematical Thinking

A

Джордан Элленберг

Algorithms and theory
RU
Statistics has played a key role in scientific understanding of the world for centuries, and in the era of big data, a basic grasp of this discipline and statistical literacy become critically important. David Spiegelhalter invites you on a fascinating, technically unburdened introduction to the theory and practice of statistics.

Statistics has played a key role in scientific understanding of the world for centuries, and in the era of big data, a basic grasp of this discipline and statistical literacy become critically important. David Spiegelhalter invites you on a fascinating, technically unburdened introduction to the theory and practice of statistics.

B

Дэвид Шпигельхалтер

Algorithms and theory
RU
Probabilistic Programming in Python: Bayesian Inference and Algorithms

Probabilistic Programming in Python: Bayesian Inference and Algorithms

A

Кэмерон Дэвидсон-Пайлон

Algorithms and theory
RU
Mathematics in Machine Learning

Mathematics in Machine Learning

A

Марк Питер Дайзенрот, А. Альдо Фейзал, Чен Сунь Он

Algorithms and theory
RU
Naked Statistics The Most Interesting Book About the Most Boring Science 2016

Naked Statistics The Most Interesting Book About the Most Boring Science 2016

F

Чарльз Уилан

Algorithms and theory
RU
Big Data. Why, What, and How?

Big Data. Why, What, and How?

A

Алена Запорожан

AI and ML
RU
Biometrics in MS Excel: A Study Guide

Biometrics in MS Excel: A Study Guide

A

Е. Я. Лебедько, А. М. Хохлов, Д. И. Барановский, О. М. Гетманец

Algorithms and theory
RU
Data Analysis Workshop with Python and R

Data Analysis Workshop with Python and R

A

О.А. Баюк, М.Р. Исаева, М.О. Самсонкин

AI and ML
RU
Computer Data Analysis

Computer Data Analysis

A

Ю.Н. Тюрин, А.А. Макаров

AI and ML
EN
Statistics Every Programmer Needs

Statistics Every Programmer Needs

A

Gary Sutton

Algorithms and theory
EN
Statistics Slam Dunk: Statistical Analysis with R on Real NBA Data

Statistics Slam Dunk: Statistical Analysis with R on Real NBA Data

A

Gary Sutton

Algorithms and theory
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