Vincent Austin Hall

Coding with ChatGPT and Other LLMs

Navigate LLMs for effective coding, debugging, and AI-driven development

• Broschiertes Buch

Produktbeschreibung

Leverage LLM (large language models) for developing unmatched coding skills, solving complex problems faster, and implementing AI responsibly Key Features: - Understand the strengths and weaknesses of LLM-powered software for enhancing performance while minimizing potential issues - Grasp the ethical considerations, biases, and legal aspects of LLM-generated code for responsible AI usage - Boost your coding speed and improve quality with IDE integration - Purchase of the print or Kindle book includes a free PDF eBook Book Description: Keeping up with the AI revolution and its application in coding can be challenging, but with guidance from AI and ML expert Dr. Vincent Hall-who holds a PhD in machine learning and has extensive experience in licensed software development-this book helps both new and experienced coders to quickly adopt best practices and stay relevant in the field. You'll learn how to use LLMs such as ChatGPT and Bard to produce efficient, explainable, and shareable code and discover techniques to maximize the potential of LLMs. The book focuses on integrated development environments (IDEs) and provides tips to avoid pitfalls, such as bias and unexplainable code, to accelerate your coding speed. You'll master advanced coding applications with LLMs, including refactoring, debugging, and optimization, while examining ethical considerations, biases, and legal implications. You'll also use cutting-edge tools for code generation, architecting, description, and testing to avoid legal hassles while advancing your career. By the end of this book, you'll be well-prepared for future innovations in AI-driven software development, with the ability to anticipate emerging LLM technologies and generate ideas that shape the future of development. What You Will Learn: - Utilize LLMs for advanced coding tasks, such as refactoring and optimization - Understand how IDEs and LLM tools help coding productivity - Master advanced debugging to resolve complex coding issues - Identify and avoid common pitfalls in LLM-generated code - Explore advanced strategies for code generation, testing, and description - Develop practical skills to advance your coding career with LLMs Who this book is for: This book is for experienced coders and new developers aiming to master LLMs, data scientists and machine learning engineers looking for advanced techniques for coding with LLMs, and AI enthusiasts exploring ethical and legal implications. Tech professionals will find practical insights for innovation and career growth in this book, while AI consultants and tech hobbyists will discover new methods for training and personal projects. Table of Contents - What is ChatGPT and What are LLMs? - Unleashing the Power of LLMs for Coding: A Paradigm Shift - Code Refactoring, Debugging, and Optimization: A Practical Guide - Demystifying Generated Code for Readability - Addressing Bias and Ethical Concerns in LLM-Generated Code - Navigating the Legal Landscape of LLM-Generated Code - Security Considerations and Measures - Limitations of Coding with LLMs - Cultivating Collaboration in LLM-Enhanced Coding - Expanding the LLM Toolkit for Coders: Beyond LLMs - Helping Others and Maximizing Your Career with LLMs - The Future of LLMs in Software Development

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 304
• Erscheinungstermin: 29. November 2024
• Englisch
• Abmessung: 235mm x 191mm x 16mm
• Gewicht: 572g
• ISBN-13: 9781805125051
• ISBN-10: 1805125052
• Artikelnr.: 72186405

Autorenporträt

Dr. Vincent Austin Hall is a computer science lecturer at Birmingham Newman University and CEO of Build Intellect Ltd, an AI consultancy. Build Intellect works closely with ABT News LTD, based in Reading, England. He holds a physics degree from the University of Leeds, an MSc in biology, chemistry, maths, and coding from Warwick, and a PhD in machine learning and chemistry, also from Warwick, where he developed licensed software for pharma applications. With experience in tech firms and academia, he's worked on ML projects in the automotive and medtech sectors. He supervises dissertations at the University of Exeter, consults on AI strategies, coaches students and professionals, and shares insights through blogs and YouTube content.