- Добавил: literator
- Дата: 27-08-2024, 14:37
- Комментариев: 0
Название: Machine Learning with Python
Автор: Tarkeshwar Barua, Kamal Kant Hiran, Ritesh Kumar Jain, Ruchi Doshi
Издательство: De Gruyter
Год: 2024
Страниц: 486
Язык: английский
Формат: pdf (true)
Размер: 40.4 MB
This book explains how to use the programming language Python to develop Machine Learning and Deep Learning tasks. Machine Learning (ML) is a discipline within the field of Artificial Intelligence (AI) that concentrates on the creation of algorithms and models, allowing computer systems to acquire knowledge and make forecasts or choices without the need for explicit programming. The primary objective of ML is to empower computers to autonomously learn and enhance their performance based on experience or data. ML, a branch of AI, enables computers to acquire knowledge and reach conclusions without the need for explicit instructions. This revolutionary discipline encompasses different methodologies, each designed to address specific learning situations. The main forms of ML comprise supervised learning, unsupervised learning, and reinforcement learning, each providing distinct approaches and applications for solving various problems. Python, a widely used general-purpose interpreted programming language, has gained immense popularity. It boasts a dynamic type system, automatic memory management, and supports multiple programming paradigms such as imperative, functional, and procedural. Python enables the creation of automated solutions for various tasks. Currently, major IT companies including Google, Microsoft, and Apple rely on Python as their primary programming language. Notably, Python stands out as the easiest programming language to learn within a short period of time. It empowers developers to build a wide range of applications, such as desktop, web, and mobile, with minimal coding effort, thanks to the abundance of frameworks and libraries available.
Автор: Tarkeshwar Barua, Kamal Kant Hiran, Ritesh Kumar Jain, Ruchi Doshi
Издательство: De Gruyter
Год: 2024
Страниц: 486
Язык: английский
Формат: pdf (true)
Размер: 40.4 MB
This book explains how to use the programming language Python to develop Machine Learning and Deep Learning tasks. Machine Learning (ML) is a discipline within the field of Artificial Intelligence (AI) that concentrates on the creation of algorithms and models, allowing computer systems to acquire knowledge and make forecasts or choices without the need for explicit programming. The primary objective of ML is to empower computers to autonomously learn and enhance their performance based on experience or data. ML, a branch of AI, enables computers to acquire knowledge and reach conclusions without the need for explicit instructions. This revolutionary discipline encompasses different methodologies, each designed to address specific learning situations. The main forms of ML comprise supervised learning, unsupervised learning, and reinforcement learning, each providing distinct approaches and applications for solving various problems. Python, a widely used general-purpose interpreted programming language, has gained immense popularity. It boasts a dynamic type system, automatic memory management, and supports multiple programming paradigms such as imperative, functional, and procedural. Python enables the creation of automated solutions for various tasks. Currently, major IT companies including Google, Microsoft, and Apple rely on Python as their primary programming language. Notably, Python stands out as the easiest programming language to learn within a short period of time. It empowers developers to build a wide range of applications, such as desktop, web, and mobile, with minimal coding effort, thanks to the abundance of frameworks and libraries available.