MLI Generative AI Series Series

AI Revealed

Theory • Applications • Ethics

Paperback
November 2024
9781501523335
More details
  • Publisher
    Mercury Learning and Information
  • Published
    13th November
  • ISBN 9781501523335
  • Language English
  • Pages 184 pp.
  • Size 6" x 9"
$41.99
E-Book

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November 2024
9781501520631
More details
  • Publisher
    Mercury Learning and Information
  • Published
    18th November
  • ISBN 9781501520631
  • Language English
  • Pages 184 pp.
  • Size 6" x 9"
$41.99
Lib E-Book

Library E-Books

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November 2024
9781501520679
More details
  • Publisher
    Mercury Learning and Information
  • Published
    18th November
  • ISBN 9781501520679
  • Language English
  • Pages 184 pp.
  • Size 6" x 9"
$165.00

This book is a guide to navigating the ever-changing landscape of artificial intelligence. It is designed for both novices and seasoned professionals, covering a wide range of topics from fundamental concepts to cutting-edge advancements. Readers will investigate the principles of machine learning, explore the intricacies of deep learning architectures, and discover the applications of natural language processing and computer vision. Through concise explanations and practical examples, readers will gain the knowledge and skills necessary to confidently navigate the dynamic field of artificial intelligence. Additionally, the text examines real-world case studies and addresses important ethical issues, providing valuable insights into the ethical implications and societal impacts of technology.

FEATURES:

  • Practical applications and case studies with a section on use cases across various industries, including healthcare, finance, transportation, and retail.
  • Actionable steps for getting started with AI include how to set up an AI development environment, learning Python for AI applications, and utilizing popular AI libraries.
  • Resources for further study including, AI online courses, AI communities and forums, and recommended books essentially, a roadmap for continuous learning.

1: Introduction to Artificial Intelligence
2: Foundations of Machine Learning
3: Deep Learning and Neural Networks
4: Natural Language Processing (NLP)
5: Computer Vision
6: Ethics and Bias in AI
7: AI in Practice Industry Case Studies
8: Future of AI and Emerging Technologies
9: Getting Started with AI Development
Appendix A: Overview Of the Lisp Programming Language
Appendix B: Resources and Community
Index

Erik L. Herman

Erik L. Herman is a Technical Trainer, Instructional Designer, and Content Developer with expertise spanning technical training, e-learning, and content development across diverse domains such as cloud computing, data analytics, and fraud detection.

AI; Deep Learning; Machine Learning; Natural Language Processing; Neural Networks; Computer Vision; Ethics