Master AI application development with practical no-code tools and clear guidance. Learn neural networks, decision trees, transfer learning, and use ChatGPT and DALL-E APIs effectively.

Key Features

• Comprehensive coverage of practical AI tools and techniques for hands-on application building
• Focus on beginner-friendly no-code solutions to lower barriers and accelerate learning speed
• Step-by-step integration of advanced AI models like ChatGPT and DALL-E through real coding examples

Book Description

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.

What you will learn

• Understand core AI concepts and foundational neural network designs
• Install and configure key AI tools like KNIME and AutoKeras
• Build and train decision trees with boosting for better accuracy
• Develop convolutional neural networks for image classification
• Apply transfer learning techniques to enhance AI model results
• Use ChatGPT and DALL-E APIs to create innovative AI applications

Who this book is for

Ideal for beginner to intermediate AI enthusiasts, developers, and data scientists interested in practical AI application development. Readers should have basic programming knowledge, ideally in Python, and an understanding of fundamental AI concepts. No prior experience with no-code AI tools is necessary, but familiarity with data analysis basics will be helpful. The book is suited for learners eager to transition from theory to hands-on AI development using accessible software and APIs.