Buy Developing AI Applications: Beginner-Friendly Guide to Building AI Solutions from Scratch with No-Code Tools (Rheinwerk Computing)

Developing AI Applications: Beginner-Friendly Guide to Building AI Solutions from Scratch with No-Code Tools (Rheinwerk Computing)

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From the Publisher

Create your own AI applications, with your own data!

Use custom datasets to develop your own AI applications!

Artificial intelligence has already found its way into our daily lives and all signs point to AI becoming even more important in the future. If you understand how this technology works, you can identify new potential applications in your field. AI can evaluate, group, and classify your existing date and provide you with insights into future events.

In this book, you’ll learn about relevant AI methods and implement an application for each of these methods yourself. You will use the KNIME platform—ideal for integrating your own data from different sources and evaluating it using purely graphical programming. We also introduce you to the world of TensorFlow and AutoKeras and show you how to create applications using simple Python code. These tried-and-tested projects have proven to be effective, both to help you learn and to solve real-world problems.

You will enrich your skills with a modern toolbox that you can use for machine learning in fields such as data analysis, controlling, and engineering. All code examples are available for download; Jupyter notebooks make it easier to work with the material in the book. Get started with your own AI now!

KNIME and Python
ChatGPT and DALL-E
Artificial neural networks (ANN)
Transfer learning
Anomaly detection
Text and image classification
Cluster analysis
Reinforcement learning

Inside the book:

This book is designed for anyone looking to get started creating basic AI applications. Prior knowledge of AI algorithms, platforms like KNIME, or the Python language are not required. The book will provide the building blocks you need to modify Python programs for your specific problems and datasets.

Practical, hands-on instructions for AI application development using no-code tools and Python
The perfect mix of theory and applied knowledge
Coverage of key AI models and algorithms
Comprehensive index to help you find what you’re looking for
Numerous screenshots, illustrations, diagrams, tables, and info boxes with tips
All exercises available for download with sample data, code, and Jupyter notebooks

Meet the author:

Metin Karatas is an electrical and information technology engineer. He was the first person to teach AI when it was established as a subject in Bavarian schools and he’s a member of the AI curriculum commission in Bavaria. Metin also teaches programming, electrical engineering, project management, and other subjects at a technical school for vocational training. He is enthusiastic about researching cutting-edge technologies and combining theoretical understanding with practical experience.

	Getting Started with Python: Beginner's Guide	Python 3: The Comprehensive Guide	AI-Assisted Coding: The Practical Guide	Generative AI with Python: The Developer’s Guide	Programming Neural Networks with Python: The Practical Guide

Customer Reviews	6	158	—	—	—
Price	$30.68	$41.31	$33.13	$50.25	$47.45
What is it? (What does it teach)	A beginner’s guide to Python!	The ultimate Python 3 guide for all levels!	The practical guide to AI pair programming!	Develop your own gen AI applications with Python!	Your practical introduction to programming neural networks!
What you'll learn?	Learn the fundamentals of Python programming—from variables and loops to functions and modules—and apply your skills to build applications, databases, and graphical user interfaces.	Learn to write effective Python code. Cover core concepts like functions, modularization, and object orientation, and explore data types. Dive into advanced topics, including Django and GUIs.	Learn to optimize your software development with AI, using tools like ChatGPT, GitHub Copilot, and OpenHands to generate code, refactor programs, debug scripts, and enhance tasks like database design, unit testing, and documentation.	Learn to to work with pretrained LLM and NLP models on Hugging Face and LangChain, create vector databases, implement retrieval-augmented generation, and add agentic systems using frameworks like crewAI and AutoGen.	Learn to program, train, and optimize neural networks using Python, covering key concepts like algorithms, activation functions, and transfer learning, while providing a practical introduction to AI, machine learning, and deep learning.
Who is this book for?	Professional programmers without prior experience in Python.	Python programmers	Developers	Python developers	Developers, data analysts, and engineers
Key Features?	Bite-sized exercises, a continuous game project, and downloadable code examples.	Step-by-step instructions and downloadable code are available.	Step-by-step instructions and examples.	Step-by-step instructions and detailed listings, with downloadable code examples.	Step-by-step instructions, color diagrams, code listings, sample applications, and downloadable projects for hands-on experimentation.
Level of difficulty?	Designed for beginners with no prior Python experience, this book teaches how to use the language to develop simple applications.	Beginners to professional programmers.	This book helps experienced programmers enhance efficiency by integrating AI pair programming tools into their workflow.	Python programming is a prerequisite for this book because the language is central to most AI systems.	This book caters to both beginners with a crash course in Python and mathematical concepts, and more advanced readers eager to start programming neural networks.