• Books
  • Tag: machine learning

Books — machine learning

RU
Data in the fight against customer churn. Analytics, dataset, metrics, and segmentation.

Data in the fight against customer churn. Analytics, dataset, metrics, and segmentation.

A

Карл Голд

AI and ML
RU
Deep Reinforcement Learning: Theory and Practice in Python

Deep Reinforcement Learning: Theory and Practice in Python

A

Лаура Грессер, Ван Лун Кенг

AI and ML
RU
Deep Learning with R and Keras 2022 by Chollet

Deep Learning with R and Keras 2022 by Chollet

A

Ф. Шолле

AI and ML
RU
Deep Learning. The Shortest and Clearest Course

Deep Learning. The Shortest and Clearest Course

A

Джон Д. Келлехер

AI and ML
RU
Deep Learning

Deep Learning

A

Николенко С., Кадурин А., Архангельская Е.

AI and ML
RU
Generative Deep Learning 2

Generative Deep Learning 2

A
AI and ML
RU
How ChatGPT Works? A Deep Dive into the Principles and Capabilities of the World's Most Famous Neural Network

How ChatGPT Works? A Deep Dive into the Principles and Capabilities of the World's Most Famous Neural Network

B

Стивен Вольфрам

AI and ML
RU
Artificial intelligence is entering an era of maturity. Slowly.

Artificial intelligence is entering an era of maturity. Slowly.

B

Томас Дэвенпорт

AI and ML
RU
The Master Algorithm: How Machine Learning Will Change Our World

The Master Algorithm: How Machine Learning Will Change Our World

A

Педро Домингос

Algorithms and theory
RU
Introduction to Neural Network Modeling

Introduction to Neural Network Modeling

A

А. П. Сергеев, Д. А. Тарасов

AI and ML
RU
Introduction to Machine Learning with Python. A Guide for Data Science Professionals

Introduction to Machine Learning with Python. A Guide for Data Science Professionals

A

Андреас Мюллер, Сара Гвидо

AI and ML
RU
Introduction to Artificial Intelligence

Introduction to Artificial Intelligence

A

А.В. Остроух

AI and ML
RU
Meta-learning. Applications in AutoML and Data Science

Meta-learning. Applications in AutoML and Data Science

A

Павел Браздил, Ян ван Рейн, Карлос Соарес, Хоакин Ваншорен

AI and ML
RU
Biological and Computer Vision

Biological and Computer Vision

A

Гэбриел Крейман

AI and ML
RU
Keras deep learning library Neural network implementation

Keras deep learning library Neural network implementation

D

Антонио Джулли, Суджит Пал

AI and ML
RU
Terrence Sejnowski. The Machine Learning Anthology. The Most Important AI Research of the Last 60 Years

Terrence Sejnowski. The Machine Learning Anthology. The Most Important AI Research of the Last 60 Years

A

Терренс Сейновски

AI and ML
RU
Analytics in Power BI with R and Python. Data Loading, Transformation, and Visualization

Analytics in Power BI with R and Python. Data Loading, Transformation, and Visualization

A

Райан Уэйд

AI and ML
RU
Data Analysis in Science and Engineering. Machine Learning, Dynamical Systems and Control

Data Analysis in Science and Engineering. Machine Learning, Dynamical Systems and Control

A

Стивен Л. Брантон, Дж. Натан Куц

AI and ML
RU
Data Science Algorithms and Their Practical Implementation in Python

Data Science Algorithms and Their Practical Implementation in Python

B

А. В. Протодьяконов, П. А. Пылов, В. Е. Садовников

AI and ML
RU
Algorithms Informally. A Guide for Beginner Pythonists

Algorithms Informally. A Guide for Beginner Pythonists

A

Брэдфорд Такфилд

Algorithms and theory
RU
GPT-4. A Guide to Using the OpenAI API

GPT-4. A Guide to Using the OpenAI API

A

Аймен Эль Амри

AI and ML
RU
Probabilistic Programming in Practice

Probabilistic Programming in Practice

A

Ави Пфеффер

Algorithms and theory
RU
Grokking Deep Learning

Grokking Deep Learning

A

Эндрю Траск

AI and ML
EN
The Elements of Differentiable Programming

The Elements of Differentiable Programming

A

Mathieu Blondel, Vincent Roulet

AI and ML
EN
Text Analytics with Python: A Practitioner’s Guide to Natural Language Processing, Second Edition

Text Analytics with Python: A Practitioner’s Guide to Natural Language Processing, Second Edition

A

Dipanjan Sarkar

AI and ML
EN
Statistics Every Programmer Needs

Statistics Every Programmer Needs

A

Gary Sutton

Algorithms and theory
EN
Scaling Python with Dask: From Data Science to Machine Learning

Scaling Python with Dask: From Data Science to Machine Learning

A

Holden Karau, Mika Kimmins

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

Python for Data Science For Dummies, 3rd Edition

A

John Paul Mueller, Luca Massaron

AI and ML
EN
Python and R for the Modern Data Scientist: The Best of Both Worlds

Python and R for the Modern Data Scientist: The Best of Both Worlds

A

Rick J. Scavetta, Boyan Angelov

AI and ML
EN
Principles of Soft Computing Using Python Programming: Learn How to Deploy Soft Computing Models in Real World Applications

Principles of Soft Computing Using Python Programming: Learn How to Deploy Soft Computing Models in Real World Applications

A

Gypsy Nandi

AI and ML
RU
Practical Statistics for Data Science Professionals: 50+ Essential Concepts Using R and Python

Practical Statistics for Data Science Professionals: 50+ Essential Concepts Using R and Python

A

Питер Брюс, Эндрю Брюс, Питер Гедек

Algorithms and theory
EN
Practical Discrete Mathematics: Discover math principles that fuel algorithms for computer science and machine learning with Python

Practical Discrete Mathematics: Discover math principles that fuel algorithms for computer science and machine learning with Python

A

Ryan T. White, Archana Tikayat Ray

Algorithms and theory
RU
Building Machine Learning Systems with Python. 2nd Edition

Building Machine Learning Systems with Python. 2nd Edition

A

Луис Педро Коэльо, Вилли Ричарт

AI and ML
RU
media books book-kaggle-machine-learning-and-data-analysis

media books book-kaggle-machine-learning-and-data-analysis

F

Конрад Банахевич, Лука Массарон

AI and ML
RU
Big Data Analysis. Technologies and Methods

Big Data Analysis. Technologies and Methods

B

Не указан

AI and ML
EN
Machine Learning Simplified: A Gentle Introduction to Supervised Learning

Machine Learning Simplified: A Gentle Introduction to Supervised Learning

A

Andrew Wolf

AI and ML
EN
Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python

Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python

A

Hariom Tatsat, Sahil Puri, Brad Lookabaugh

AI and ML
EN
Machine Learning and Data Science: Fundamentals and Applications

Machine Learning and Data Science: Fundamentals and Applications

A

Prateek Agrawal, Charu Gupta, Anand Sharma, Vishu Madaan, Nisheeth Joshi

AI and ML
EN
Java Deep Learning Essentials

Java Deep Learning Essentials

A

Yusuke Sugomori

AI and ML
EN
Introduction to Deep Learning Using R: A Step-by-Step Guide to Learning and Implementing Deep Learning Models Using R

Introduction to Deep Learning Using R: A Step-by-Step Guide to Learning and Implementing Deep Learning Models Using R

A

Taweh Beysolow II

AI and ML
EN
Intro to Python® for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud

Intro to Python® for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud

A

Paul Deitel & Harvey Deitel

AI and ML
EN
Statistical Process Monitoring using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications

Statistical Process Monitoring using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications

A

Fouzi Harrou, Ying Sun, Amanda S. Hering, Muddu Madakyaru, Abdelkader Dairi

Algorithms and theory
EN
Hands-on TinyML: Harness the power of Machine Learning on the edge devices

Hands-on TinyML: Harness the power of Machine Learning on the edge devices

A

Rohan Banerjee

Embedded systems
EN
Domain-Specific Languages in R: Advanced Statistical Programming

Domain-Specific Languages in R: Advanced Statistical Programming

A

Thomas Mailund

Programming languages
EN
Deep Learning with Python

Deep Learning with Python

A

Франсуа Шолле

AI and ML
EN
Data Science: The Hard Parts. Techniques for Excelling at Data Science

Data Science: The Hard Parts. Techniques for Excelling at Data Science

A

Daniel Vaughan

AI and ML
EN
Data Wrangling with SQL: A hands-on guide to manipulating, wrangling, and engineering data using SQL

Data Wrangling with SQL: A hands-on guide to manipulating, wrangling, and engineering data using SQL

A

Raghav Kandarpa, Shivangi Saxena

AI and ML
EN
Data Science and Machine Learning Interview Questions using Python: A Complete Question Bank to Crack Your Interview

Data Science and Machine Learning Interview Questions using Python: A Complete Question Bank to Crack Your Interview

A

Vishwanathan Narayanan

AI and ML
EN
Approaching (Almost) Any Machine Learning Problem

Approaching (Almost) Any Machine Learning Problem

A

Abhishek Thakur

AI and ML
EN
Introduction to Python

Introduction to Python

A

James P. Meyer

Programming languages
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