Mastering Self-Learning AI

Artificial Intelligence, Machine Learning, Neural Networks, Deep Learning, Reinforcement Learning, Data Mining, Algorithms, Supervised Learning, Unsupervised Learning, Natural Language Processing, Com

씨익북스 편집부 지음

타우루스 2025년 02월 12일 출간

작품소개

책소개

"Mastering Self-Learning AI is an essential guide for anyone interested in delving into the transformative world of artificial intelligence. This comprehensive resource covers a wide array of topics, including Machine Learning, Neural Networks, and Deep Learning, making it suitable for both beginners and seasoned practitioners.

From the fundamental principles of algorithms to the complexities of Reinforcement Learning, this book offers a structured approach to understanding how AI systems learn and adapt. Readers will explore vital concepts like Supervised and Unsupervised Learning, Natural Language Processing, and Computer Vision, all of which are pivotal in creating intelligent systems that can process data and make decisions.

The book emphasizes practical applications, showcasing techniques such as Feature Engineering, Model Evaluation, and Training Techniques. It also delves into advanced methodologies like Data Augmentation and Transfer Learning, which are critical for enhancing model performance and generalization.

Moreover, Mastering Self-Learning AI addresses the ethical implications of AI technologies, guiding readers through the nuances of responsible AI development. As automation becomes increasingly prevalent, the book discusses the intersection of AI with Big Data, Cloud Computing, and Robotics, illustrating how these fields converge to create innovative solutions.

With hands-on programming examples in Python, readers will build their confidence and skills as they work through real-world projects. The inclusion of Predictive Analytics further empowers learners to harness AI for data-driven decision-making.

Whether you're looking to kick-start a career in AI, enhance your knowledge, or develop cutting-edge technologies, Mastering Self-Learning AI equips you with the necessary tools and insights to navigate this rapidly evolving landscape. Join the journey to unlock the potential of self-learning AI and be at the forefront of tomorrow's technological advancements."

목차

"1. Introduction to AI Concepts
2. The Evolution of Machine Learning
3. Understanding Neural Networks
4. Deep Learning Fundamentals
5. The Role of Reinforcement Learning
6. Data Mining Techniques
7. Algorithms in AI: An Overview
8. Supervised Learning Explained
9. Unsupervised Learning Strategies
10. Natural Language Processing Essentials
11. Computer Vision Basics
12. Feature Engineering Techniques
13. Model Evaluation Metrics
14. Training Techniques for AI Models
15. Data Augmentation Methods
16. Transfer Learning Explained
17. The Ethics of AI Development
18. Robotics and AI Integration
19. Predictive Analytics in Action
20. Big Data: The New Frontier
21. Cloud Computing for AI Solutions
22. Automation in AI Applications
23. Programming Languages for AI
24. Python for Machine Learning
25. Building Your First AI Model
26. Advanced Neural Network Architectures
27. Hyperparameter Tuning Techniques
28. Understanding Overfitting and Underfitting
29. The Importance of Data Quality
30. Visualization Techniques for AI Data
31. Real-World Applications of AI
32. Case Studies in Machine Learning
33. Challenges in AI Implementation
34. Future Trends in AI and ML
35. Open Source Tools for AI Development
36. AI in Healthcare: Opportunities and Challenges
37. AI in Finance: Transforming the Industry
38. Ethical Considerations in AI Deployment
39. The Impact of AI on Employment
40. Building Robust AI Systems
41. Collaborative Filtering in Recommender Systems
42. Time Series Analysis with Machine Learning
43. Natural Language Understanding vs. Processing
44. The Role of AI in Cybersecurity
45. Integrating AI with IoT
46. The Science of Data-Driven Decision Making
47. AI and Environmental Sustainability
48. Leveraging AI in Marketing Strategies
49. The Intersection of AI and Augmented Reality
50. Preparing for a Career in AI and Machine Learning"

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