Artificial Intelligence with Python
By: Teik Toe Teoh, Zheng Rong
About This Book
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.
AI Overview
The book "Artificial Intelligence with Python" by Teik Toe Teoh and Zheng Rong is a comprehensive guide to learning both Python programming and Artificial Intelligence (AI). Here is a detailed overview of the book:
Key Themes
- Introduction to AI: The book provides an introduction to the fundamental concepts of artificial intelligence, making it accessible to beginners.
- Python Programming: It covers the basics of Python programming, ensuring readers have a solid foundation in the language before diving into AI.
- Machine Learning: The book delves into various machine learning techniques, including decision trees, artificial neural networks, kernel learning, Bayesian learning, ensemble methods, dimension reduction, metric learning, reinforcement learning, meta learning, and imitation learning.
- Advanced Concepts: It includes advanced topics such as recurrent neural networks (RNNs), deep learning models, feature selection and engineering, and AI on the cloud.
- Practical Applications: The book emphasizes practical applications, including the creation of intelligent apps and chatbots, and explores the integration of AI with Big Data.
Plot Summary
The book is structured to guide readers through the entire process of learning AI with Python. It starts with an introduction to Python programming and gradually moves on to more advanced AI concepts. The chapters are designed to be both theoretical and practical, providing readers with hands-on experience in implementing AI models using Python.
Critical Reception
While specific reviews from the book are not provided in the sources, the book is described as a "practical guide" and is part of a series focused on machine learning foundations, methodologies, and applications. This suggests that it is well-regarded for its practical approach and comprehensive coverage of AI topics.
Additional Information
- Editions: There are multiple editions of the book, with the most recent ones updated to Python 3.x and including new chapters on advanced AI topics.
- Target Audience: The intended readership includes research students and researchers in computer science, computer engineering, electrical engineering, data science, and related areas.
In summary, "Artificial Intelligence with Python" by Teik Toe Teoh and Zheng Rong is a thorough guide that covers both the basics of Python programming and advanced AI concepts, making it a valuable resource for those interested in machine learning and AI.