Essentials of Python for Artificial Intelligence and Machine Learning

Pramod Gupta (u. a.)

ISBN 10: 3031437241 / ISBN 13: 9783031437243

Published by Springer, 2024

About this Item

Essentials of Python for Artificial Intelligence and Machine Learning | Pramod Gupta (u. a.) | Buch | xix | Englisch | 2024 | Springer | EAN 9783031437243 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 127364640

Bibliographic Details

• Title: Essentials of Python for Artificial Intelligence and Machine Learning
• Publisher: Springer
• Publication Date: 2024
• Language: English
• ISBN 10: 3031437241
• ISBN 13: 9783031437243
• Binding: Buch
• Condition: Neu
• Dimensions: 246W x 173H x 34D millimeters 246 millimeters width by 173 millimeters height by 34 millimeters depth
• Weight: 1059 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI). The authors explore the use of Python’s advanced module features and apply them in probability, statistical testing, signal processing, financial forecasting, and various other applications. This includes mathematical operations with array data structures, Data Manipulation, Data Cleaning, machine learning, Data pipeline, probability density functions, interpolation, visualization, and other high-performance benefits using the core scientific packages NumPy, Pandas, SciPy, Sklearn/Scikit learn and Matplotlib. Readers will gain a deep understanding with problem-solving experience on these powerful platforms when dealing with engineering and scientific problems related to Machine Learning and Artificial Intelligence. Several examples of real problems using these techniques are provided along with examples. The authors also focus on the best practices in theindustry on using Python for AI and ML. Deployment on a cloud infrastructure is described in detail (with code) to emphasize real scenarios.

About the Author

Pramod Gupta has more than 20 years of experience as a researcher and academician in various organizations including work with NASA, GE, VISA, and University of California and startups. He has a PhD from McMaster University in Electrical and Computer Engineering with specialization in Neuro-Control of Robotic Manipulators. He has more than 40 publications on these subjects. His research areas include, Neural Networks, Machine Learning, Artificial Intelligence, Data Modeling and Analytics and Data mining. Presently, he is working as adjunct faculty and independent data science consultant.

Anupam Bagchi has more than 20 years of experience working in the Silicon Valley in various roles. He has experience in big companies like IBM and Stanford, as well as start-ups that have produced cutting edge technologies. Though, most of his carrier has primarily been as a software engineer at various seniority levels, he has been working as an active data scientist for the past 10 years. His experience spans various domains such as XML parsing, content management, big data, ecommerce, internet of things (IoT), networking, artificial intelligence applied to bioinformatics and business intelligence applied to travel industry.