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کنکور کامپیوترکتاب‌های رشته کامپیوترکتاب های هوش مصنوعیکتاب Artificial Intelligence for Dummies
کتاب Artificial Intelligence for Dummiesکتاب Artificial Intelligence for Dummies
دانلود کتاب (free download)
ناشر : For Dummies
تاریخ انتشار : 1397/01/28
نسخه : 1
زبان : انگلیسی
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کنکور کامپیوترکتاب‌های رشته کامپیوترکتاب های هوش مصنوعیکتاب Artificial Intelligence for Dummies
کتاب Artificial Intelligence for Dummies

کتاب Artificial Intelligence for Dummies

نویسنده : John Mueller , Luca Massaron
339 صفحه
دانلود کتاب (free download)
English Title : Ai For Dummies (For Dummies (Computer/Tech)) 1st Edition
عنوان فارسی : کتاب هوش مصنوعی برای آدمک ها (برای آدمک ها (کامپیوتر/فناوری))

Description

The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today.

Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field.

  • Learn about what AI has contributed to society
  • Explore uses for AI in computer applications
  • Discover the limits of what AI can do
  • Find out about the history of AI

The world of AI is fascinating—and this hands-on guide makes it more accessible than ever!

Table of contents

Introduction
Part 1: Introducing AI
Chapter 1: Introducing AI
Chapter 2: Defining the Role of Data
Chapter 3: Considering the Use of Algorithms
Chapter 4: Pioneering Specialized Hardware
Part 2: Considering the Uses of AI in Society
Chapter 5: Seeing AI Uses in Computer Applications
Chapter 6: Automating Common Processes
Chapter 7: Using AI to Address Medical Needs
Chapter 8: Relying on AI to Improve Human Interaction
Part 3: Working with Software-Based AI Applications
Chapter 9: Performing Data Analysis for AI
Chapter 10: Employing Machine Learning in AI
Chapter 11: Improving AI with Deep Learning
Part 4: Working with AI in Hardware Applications
Chapter 12: Developing Robots
Chapter 13: Flying with Drones
Chapter 14: Utilizing the AI-Driven Car
Part 5: Considering the Future of AI
Chapter 15: Understanding the Nonstarter Application
Chapter 16: Seeing AI in Space
Chapter 17: Adding New Human Occupations
Part 6: The Part of Tens
Chapter 18: Ten AI-Safe Occupations
Chapter 19: Ten Substantial Contributions of AI to Society
Chapter 20: Ten Ways in Which AI Has Failed
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John Mueller

John Mueller

John Mueller is a freelance author and technical editor. He has writing in his blood, having produced 117 books and over 600 articles to date. He has also written his second children's book recently, Tail of the Wuggly Bump. His technical topics range from networking to artificial intelligence and from database management to heads down programming. His most recent book is "Machine Learning for Dummies, 2nd Edition." His technical editing skills have helped over 70 authors refine the content of their manuscripts. You can reach John on the Internet at John@JohnMuellerBooks.com and his Web site at: http://www.johnmuellerbooks.com. Make sure to read his blog at http://blog.johnmuellerbooks.com to obtain the latest book information, updates, and extra materials.
Luca Massaron

Luca Massaron

Luca Massaron is a data scientist and a research director specialized in multivariate statistical analysis, machine learning and customer insight with over a decade of experience in solving real world problems and in generating value for stakeholders by applying reasoning, statistics, data mining and algorithms. From being a pioneer of Web audience analysis in Italy to achieving the rank of top ten data scientist at competitions held by kaggle.com, he has always been passionate about everything regarding data and analysis and about demonstrating the potentiality of data-driven knowledge discovery to both experts and non-experts. Favouring simplicity over unnecessary sophistication, he believes that a lot can be achieved in data science just by doing the essential.
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