Artificial Intelligence with Python, Third Edition is a complete, hands-on guide that takes you from the foundations of AI to mastering cutting-edge techniques, including Large Language Models (LLMs), Reinforcement Learning, and MLOps. This fully updated edition ensures you stay ahead with the latest AI innovations.
You'll explore machine learning algorithms, neural networks, and state-of-the-art deep learning architectures like transformers and diffusion models. You'll also learn to fine-tune open-source LLMs, work with multimodal AI, and deploy models efficiently using MLOps best practices.
Unlike many AI books that focus heavily on theoretical foundations and academic algorithms, this book is designed as a practitioner’s guide to mastering AI for real-world applications. Rather than overwhelming you with every algorithm ever created, this book prioritizes the AI techniques that matter most in industry today—from Large Language Models (LLMs) and Reinforcement Learning to MLOps and Edge AI. Whether you're a data scientist, ML engineer, or software developer, this book serves as your hands-on roadmap to building AI-powered applications, fine-tuning models, and deploying AI at scale.
By the end of this book, you'll have hands-on experience in building AI-powered applications, deploying models on the cloud and edge devices.

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Spis treści

Artificial Intelligence with Python. Master Deep Learning, Reinforcement Learning, LLMs, and Modern AI Applications - Third Edition eBook -- spis treści

• 1. Introduction to Artificial Intelligence
• 2. Essential Mathematics for AI
• 3. Core AI Concepts & Techniques
• 4. Supervised Learning with Python
• 5. Unsupervised Learning & Clustering
• 6. Ensemble Learning & Model Stacking
• 7. Neural Networks & Deep Learning Fundamentals
• 8. Convolutional Neural Networks (CNNs) for Image Recognition
• 9. Recurrent Neural Networks (RNNs) and Transformers
• 10. Generative AI & Large Language Models (LLMs)
• 11. Building a Modern AI Data Pipeline
• 12. MLOps & AI Model Deployment
• 13. Building Intelligent Agents with Reinforcement Learning
• 14. Multimodal AI & Generative Media
• 15. Edge AI & On-Device Machine Learning
• 16. AI and Big Data
• 17. AI Ethics, Bias, and Responsible AI
• 18. Building AI-Powered Chatbots
• 19. Speech Recognition & AI Voice Assistants
• 20. AI for Time Series & Forecasting
• 21. Autonomous AI Agents & Workflow Automation
• 22. Future Trends & Next-Gen AI
• 23. AI Career Pathways: Roles, Skills, and Certifications
• 24. Preparing for AI Interviews