This book opens with a clear introduction to AI fundamentals, covering its history and key concepts while guiding readers through installing essential tools like KNIME and AutoKeras. It begins by building a strong foundation in artificial neural networks and decision trees, enabling readers to grasp core AI methods. The journey then advances to convolutional layers for image classification, transfer learning, and anomaly detection, offering practical, beginner-friendly examples.
As the reader progresses, the book explores text classification, cluster analysis, and automated AI model creation with AutoKeras. Visual programming with KNIME is introduced to simplify complex AI workflows. Further chapters cover reinforcement learning and genetic algorithms, expanding the reader’s skill set and preparing them for more advanced challenges. Hands-on exercises throughout reinforce concepts and practical application.
In its final chapters, the guide dives into cutting-edge AI tools by demonstrating how to leverage ChatGPT and DALL-E APIs, including prompt engineering and API programming. It concludes with an outlook on the future of AI, equipping readers with the knowledge and confidence to build and deploy their own AI-powered applications from start to finish.

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Spis treści

Developing AI Applications. An Introduction eBook -- spis treści

• 1. Introduction
• 2. Installation
• 3. Artificial Neural Networks
• 4. Decision Trees
• 5. Convolutional Layers and Images
• 6. Transfer Learning
• 7. Anomaly Detection
• 8. Text Classification
• 9. Cluster Analysis
• 10. AutoKeras
• 11. Visual Programming Using KNIME
• 12. Reinforcement Learning
• 13. Genetic Algorithms
• 14. ChatGPT and GPT-4
• 15. DALL-E and Successor Models
• 16. Outlook