Essentials of Python for Artificial Intelligence and Machine Learning

This book provides an introduction to Python for Machine Learning and Artificial Intelligence, covering advanced module features and their applications in probability, statistical testing, signal processing, financial forecasting, and more. It emphasizes problem-solving experience with real-world examples and best practices for deploying Python on a cloud infrastructure.

Format: Hardback
Length: 509 pages
Publication date: 15 February 2024
Publisher: Springer International Publishing AG

This comprehensive book delves into the fundamentals of Python, catering to the rapidly evolving domains of Machine Learning (ML) and Artificial Intelligence (AI). Authored by experts, it explores the advanced module features of Python and applies them across a wide range of applications, including probability, statistical testing, signal processing, financial forecasting, and more. The book covers essential topics such as mathematical operations with array data structures, data manipulation, data cleaning, machine learning, data pipeline, probability density functions, interpolation, visualization, and other high-performance benefits utilizing core scientific packages like NumPy, Pandas, SciPy, Sklearn/Scikit learn, and Matplotlib. By providing hands-on problem-solving experiences, readers will gain a deep understanding of these powerful platforms and their applications in addressing engineering and scientific challenges related to ML and AI. Numerous real-world examples and case studies are included to illustrate the practical applications of Python techniques. Additionally, the authors emphasize best practices in the industry for utilizing Python in AI and ML, with a detailed explanation of deploying solutions on a cloud infrastructure. This book serves as a valuable resource for professionals, researchers, and enthusiasts seeking to leverage Python's capabilities in these cutting-edge fields.

This comprehensive book delves into the fundamentals of Python, catering to the rapidly evolving domains of Machine Learning (ML) and Artificial Intelligence (AI). Authored by experts, it explores the advanced module features of Python and applies them across a wide range of applications, including probability, statistical testing, signal processing, financial forecasting, and more. The book covers essential topics such as mathematical operations with array data structures, data manipulation, data cleaning, machine learning, data pipeline, probability density functions, interpolation, visualization, and other high-performance benefits utilizing core scientific packages like NumPy, Pandas, SciPy, Sklearn/Scikit learn, and Matplotlib. By providing hands-on problem-solving experiences, readers will gain a deep understanding of these powerful platforms and their applications in addressing engineering and scientific challenges related to ML and AI. Numerous real-world examples and case studies are included to illustrate the practical applications of Python techniques. Additionally, the authors emphasize best practices in the industry for utilizing Python in AI and ML, with a detailed explanation of deploying solutions on a cloud infrastructure. This book serves as a valuable resource for professionals, researchers, and enthusiasts seeking to leverage Python's capabilities in these cutting-edge fields.

Weight: 1059g
Dimension: 240 x 168 (mm)
ISBN-13: 9783031437243
Edition number: 1st ed. 2024