Understanding Artificial Intelligence

Machine Learning, Neural Networks, Deep Learning, Algorithms, Data Science, Natural Language Processing, Computer Vision, Robotics, Ethics, Automation, Big Data, Predictive Analytics, Supervised Learning, Unsupervised Learning

씨익북스 편집부 지음

타우루스 2025년 02월 12일 출간

작품소개

책소개

"Understanding Artificial Intelligence is a comprehensive guide that delves into the multifaceted world of AI, exploring its various components and applications across diverse fields. This book serves as an essential resource for anyone looking to grasp the fundamentals of Artificial Intelligence, including Machine Learning, Neural Networks, and Deep Learning.

The journey begins with a thorough understanding of algorithms that drive AI systems and progresses into the realms of Data Science and Natural Language Processing. Readers will learn how AI interprets and processes human language, making significant strides in communication and understanding through chatbots and virtual assistants.

A significant focus is placed on Computer Vision, showcasing how machines can perceive and interpret visual information, leading to advancements in robotics and automation. The book also discusses the ethical implications of AI, emphasizing the importance of responsible AI practices in a world increasingly influenced by intelligent systems.

In addition to theoretical concepts, the book offers practical insights into the applications of AI in various sectors, including healthcare, education, and business. By examining case studies and real-world examples, readers will understand how predictive analytics and different learning paradigms—such as supervised, unsupervised, and reinforcement learning—are transforming industries and enhancing decision-making processes.

As the landscape of work evolves, Understanding Artificial Intelligence highlights AI trends and the future of work, preparing readers for the impending changes brought about by intelligent technologies. This book is not just a technical manual; it is an invitation to engage with the ethical, societal, and economic dimensions of AI, making it a must-read for students, professionals, and anyone curious about the transformative power of artificial intelligence."

목차

"1. The Evolution of Artificial Intelligence
2. Foundations of Machine Learning
3. Understanding Neural Networks
4. Deep Learning Demystified
5. Algorithms That Power AI
6. The Role of Data Science in AI
7. Natural Language Processing Explained
8. An Introduction to Computer Vision
9. Robotics: The Future of Automation
10. Ethical Considerations in AI
11. Automation and the Workforce
12. Big Data: The Fuel for AI
13. Predictive Analytics in Action
14. Supervised Learning Techniques
15. Unsupervised Learning Essentials
16. Reinforcement Learning: Learning by Doing
17. Real-World Applications of AI
18. The Rise of Chatbots
19. AI Ethics: A Growing Concern
20. Human-Computer Interaction in the Age of AI
21. AI in Healthcare: Transforming Patient Care
22. The Impact of AI on Education
23. AI in Business: Strategies for Success
24. Current Trends in Artificial Intelligence
25. The Future of Work with AI
26. Intelligent Systems: Bridging the Gap
27. The Importance of Data Quality
28. Bias in AI and Its Implications
29. Neural Networks vs. Traditional Algorithms
30. Practical Tools for Machine Learning
31. The Science Behind Deep Learning
32. AI in Everyday Life
33. The Intersection of AI and Creativity
34. Building Trust in AI Systems
35. The Role of AI in Cybersecurity
36. AI and Climate Change: A Dual Approach
37. Ethical AI: Guidelines and Frameworks
38. Understanding AI Models and Their Limitations
39. The Role of AI in Financial Services
40. AI for Social Good: Opportunities and Challenges
41. How AI is Reshaping Supply Chains
42. The Future of Autonomous Vehicles
43. AI and the Internet of Things
44. Challenges in Implementing AI Solutions
45. The Role of AI in Marketing Strategies
46. AI in Sports Analytics
47. The Global Landscape of AI Research
48. Interdisciplinary Approaches to AI
49. The Importance of Explainable AI
50. Preparing for an AI-Driven Future"

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