Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Demystifying the Black Box: A Deep Dive into Explainable AI (XAI) and Machine Learning

Demystifying the Black Box: A Deep Dive into Explainable AI (XAI) and Machine Learning

Royce, Taylor

Paperback

Series: Books on Tech, Book 74

General Computers

ISBN13: 9798319080875
Publisher: Independently Published
Published: Apr 11 2025
Pages: 152
Weight: 0.47
Height: 0.33 Width: 6.00 Depth: 9.00
Language: English
Understanding the choices made by intricate algorithms has proven to be one of the most difficult problems in the rapidly developing field of artificial intelligence (AI). Demystifying the Black Box: A Deep Dive into Explainable AI (XAI) and Machine Learning gives readers a thorough overview of the quickly developing field of explainable AI (XAI) while taking them on an enlightening and approachable journey into the frequently enigmatic realm of artificial intelligence.

The fundamental ideas of machine learning and XAI are examined in this book, which clarifies how AI systems decide and why transparency is so important. You'll discover how to handle the intricacies of algorithms that are reshaping sectors like healthcare and banking through knowledgeable explanations, practical examples, and state-of-the-art research.

This book will provide you with the knowledge you need, whether you're a novice trying to grasp the basics of AI, an experienced data scientist aiming to go deeper into interpretability, or a decision-maker looking to adopt AI more intelligently.

Inside, you'll find:

  • Detailed explanations of intricate AI ideas, divided into manageable chunks
  • Practical methods for applying explainable AI in practical situations; insights into the most recent developments in machine learning and how they are changing the future
  • Insightful conversations about the moral and legal issues surrounding AI transparency - Useful guidance on creating transparent, equitable, and responsible AI systems

Also from

Royce, Taylor

View All

Also in

General Computers

View All