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Artificial intelligence with Python

Teoh, Teik Toe.

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Artificial intelligence with Python

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence with Python/ by Teik Toe Teoh, Zheng Rong.
Author:	Teoh, Teik Toe.
other author:	Rong, Zheng.
Published:	Singapore :Springer Singapore : : 2022.,
Description:	xiv, 336 p. :ill., digital ;24 cm.
[NT 15003449]:	Part I Python -- 1 About Python -- 2 What's Python? -- 3 An Introductory Example -- 4 Basic Python -- 5 Intermediate Python -- 6 Advanced Python -- 7 Python for data analysis -- Part II Artificial Intelligence Basics -- 8 Introduction to artificial intelligence -- 9 Data wrangling -- 10 Regression -- 11 Classification -- 12 Clustering -- 13 Association Rules -- Part III Artificial Intelligence -- Implementations -- 14 Text Mining -- 15 Image Processing -- 16 Convolutional Neural Networks -- 17 Chatbot, Speech and NLP -- 18 Deep Convolutional Generative Adversarial Network -- 19 Neural style transfer -- 20 Reinforcement learning -- 21 References.
Contained By:	Springer Nature eBook
Subject:	Python (Computer program language) -
Online resource:	https://doi.org/10.1007/978-981-16-8615-3
ISBN:	9789811686153

Artificial intelligence with Python
Teoh, Teik Toe.

Artificial intelligence with Python[electronic resource] /by Teik Toe Teoh, Zheng Rong. - Singapore :Springer Singapore :2022. - xiv, 336 p. :ill., digital ;24 cm. - Machine learning: foundations, methodologies, and applications,2730-9916. - Machine learning: foundations, methodologies, and applications..

Part I Python -- 1 About Python -- 2 What's Python? -- 3 An Introductory Example -- 4 Basic Python -- 5 Intermediate Python -- 6 Advanced Python -- 7 Python for data analysis -- Part II Artificial Intelligence Basics -- 8 Introduction to artificial intelligence -- 9 Data wrangling -- 10 Regression -- 11 Classification -- 12 Clustering -- 13 Association Rules -- Part III Artificial Intelligence -- Implementations -- 14 Text Mining -- 15 Image Processing -- 16 Convolutional Neural Networks -- 17 Chatbot, Speech and NLP -- 18 Deep Convolutional Generative Adversarial Network -- 19 Neural style transfer -- 20 Reinforcement learning -- 21 References.

Entering the field of artificial intelligence and data science can seem daunting to beginners with little to no prior background, especially those with no programming experience. The concepts used in self-driving cars and virtual assistants like Amazon's Alexa may seem very complex and difficult to grasp. The aim of Artificial Intelligence in Python is to make AI accessible and easy to understand for people with little to no programming experience though practical exercises. Newcomers will gain the necessary knowledge on how to create such systems, which are capable of executing tasks that require some form of human-like intelligence. This book introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.

ISBN: 9789811686153

Standard No.: 10.1007/978-981-16-8615-3doiSubjects--Topical Terms:

729789
Python (Computer program language)

LC Class. No.: QA76.73.P98 / T46 2022

Dewey Class. No.: 005.133

Artificial intelligence with Python
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505 0 $a Part I Python -- 1 About Python -- 2 What's Python? -- 3 An Introductory Example -- 4 Basic Python -- 5 Intermediate Python -- 6 Advanced Python -- 7 Python for data analysis -- Part II Artificial Intelligence Basics -- 8 Introduction to artificial intelligence -- 9 Data wrangling -- 10 Regression -- 11 Classification -- 12 Clustering -- 13 Association Rules -- Part III Artificial Intelligence -- Implementations -- 14 Text Mining -- 15 Image Processing -- 16 Convolutional Neural Networks -- 17 Chatbot, Speech and NLP -- 18 Deep Convolutional Generative Adversarial Network -- 19 Neural style transfer -- 20 Reinforcement learning -- 21 References.
520 $a Entering the field of artificial intelligence and data science can seem daunting to beginners with little to no prior background, especially those with no programming experience. The concepts used in self-driving cars and virtual assistants like Amazon's Alexa may seem very complex and difficult to grasp. The aim of Artificial Intelligence in Python is to make AI accessible and easy to understand for people with little to no programming experience though practical exercises. Newcomers will gain the necessary knowledge on how to create such systems, which are capable of executing tasks that require some form of human-like intelligence. This book introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.
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