Coding with ChatGPT and Other LLMs
Coding with ChatGPT and Other LLMs

Author: Dr. Vincent Austin Hall

Publisher: Packt Publishing Ltd

Published: 2024-11-29

Total Pages: 304

ISBN-13: 1805127969

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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 DescriptionKeeping 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.

Generative AI
Generative AI

Author: Martin Musiol

Publisher: John Wiley & Sons

Published: 2023-01-08

Total Pages: 315

ISBN-13: 1394205945

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An engaging and essential discussion of generative artificial intelligence In Generative AI: Navigating the Course to the Artificial General Intelligence Future, celebrated author Martin Musiol—founder and CEO of generativeAI.net and GenAI Lead for Europe at Infosys—delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space. Musiol analyzes complex and foundational topics in generative AI, breaking them down into straightforward and easy-to-understand pieces. You'll also find: Bold predictions about the future emergence of Artificial General Intelligence via the merging of current AI models Fascinating explorations of the ethical implications of AI, its potential downsides, and the possible rewards Insightful commentary on Autonomous AI Agents and how AI assistants will become integral to daily life in professional and private contexts Perfect for anyone interested in the intersection of ethics, technology, business, and society—and for entrepreneurs looking to take advantage of this tech revolution—Generative AI offers an intuitive, comprehensive discussion of this fascinating new technology.

Machine Learning with PyTorch and Scikit-Learn
Machine Learning with PyTorch and Scikit-Learn

Author: Sebastian Raschka

Publisher: Packt Publishing Ltd

Published: 2022-02-25

Total Pages: 775

ISBN-13: 1801816387

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This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn applied machine learning with a solid foundation in theory Clear, intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices Book DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP). This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learn Explore frameworks, models, and techniques for machines to learn from data Use scikit-learn for machine learning and PyTorch for deep learning Train machine learning classifiers on images, text, and more Build and train neural networks, transformers, and boosting algorithms Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who this book is for If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.

Generative AI with LangChain
Generative AI with LangChain

Author: Ben Auffarth

Publisher: Packt Publishing Ltd

Published: 2023-12-22

Total Pages: 369

ISBN-13: 1835088368

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2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.

Practical Java Programming with ChatGPT
Practical Java Programming with ChatGPT

Author: Alan S. Bluck

Publisher: Orange Education Pvt Ltd

Published: 2023-11-03

Total Pages: 409

ISBN-13: 8119416791

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How to use ChatGPT to write fast validated Java code KEY FEATURES ● Discover how to leverage Java code generated with ChatGPT to expedite the development of practical solutions for everyday programming challenges. ● Gain insight into the benefits of harnessing AI to elevate your effectiveness as a software engineer. ● Elevate your professional journey by significantly boosting your programming efficiency to swiftly produce reliable; tested code. ● Harness and validate the potential of ChatGPT; both directly through the ChatGPT Java API and indirectly by leveraging ChatGPT's Java code generation capabilities. DESCRIPTION Embark on a Fascinating Journey into AI-Powered Software Development with ChatGPT. This transformative book challenges the conventional speed of software development by showcasing a diverse array of inquiries directed at cutting-edge AI tools, including Ask AI, ChatGPT 3.5, Perplexity AI, Microsoft Bing Chatbot based on ChatGPT 4.0, and the Phed mobile app. Diving deep into the integration of Java and ChatGPT, this book provides readers with a comprehensive understanding of their synergy in programming. Each carefully crafted question serves as a testament to ChatGPT's exceptional ability to swiftly generate Java programs. The resulting code undergoes rigorous validation using the latest open-source Eclipse IDE and the Java language, empowering readers to craft efficient code in a fraction of the usual time. The journey doesn't end there—this book looks ahead to the promising future of ChatGPT, unveiling exciting potential enhancements planned by OpenAI. These innovations are poised to usher in even more formidable AI-driven capabilities for software development. WHAT WILL YOU LEARN ● Develop NLP Solutions in Java for Mathematical, Content, and Sentiment Analysis. ● Seamlessly Integrate ChatGPT with Java via OpenAI API. ● Harness AI-Powered Code Snippet Generation and Intelligent Code Suggestions. ● Leverage Rapid Idea Prototyping and Validation in Java Development. ● Empower the Creation of Tailored Java Applications. ● Enhance Efficiency and Expedite Prototyping with Instant AI Insights. WHO IS THIS BOOK FOR? This book is tailored for Java Programmers, IT consultants, Systems and Solution Architects with fundamental IT knowledge. It offers practical templates for Java programming solutions, complete with ChatGPT-powered examples. These templates empower Developers working on data processing, mathematical analysis, and document management, facilitating implementations for industries such as Manufacturing, Banking, and Insurance Companies. TABLE OF CONTENTS 1. Getting Started with ChatGPT 2. Java Programming – Best Practices as Stated by ChatGPT 3. Developing Java Code for Utilizing the ChatGPT API 4. Java Program for Using Binary Search 5. Installation of the Latest Open-source Eclipse Java IDE 6. ChatGPT Generated Java Code for Fourier Analysis 7. ChatGPT Generated Java Code for the Fast Fourier Transform 8. ChatGPT Generated Java Code for Indexing a Document 9. ChatGPT-Generated Java Code for Saltikov Particle Distribution 10. ChatGPT-Generated Java Code to Invert a Triangular Matrix 11. ChatGPT Generated Java Code to Store a Document in the IBM FileNet System 12. Conclusions and the Future of ChatGPT for Program Development 13. Appendices for Additional Questions Index

Modern Python Programming using ChatGPT
Modern Python Programming using ChatGPT

Author: Shivakumar Gopalakrishnan

Publisher: BPB Publications

Published: 2024-08-29

Total Pages: 437

ISBN-13: 936589431X

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DESCRIPTION Modern Python Programming using ChatGPT is your essential guide to leveraging Artificial Intelligence to streamline and enhance your Python development workflow across the entire software development lifecycle (SDLC). This book covers every stage, from requirements gathering and design to implementation, testing, security, deployment, and observability, demonstrating how ChatGPT can be of invaluable assistance throughout. Learn how to use ChatGPT to break down features into stories, design, and architect software, implement AI-generated code snippets, write clean and maintainable code, test and secure applications, deploy efficiently, and monitor performance. This comprehensive guide shows you how to integrate ChatGPT seamlessly into every stage of your Python projects. Discover how ChatGPT can automate repetitive tasks, generate high-quality code snippets, provide instant debugging tips, and ensure your code adheres to industry standards and best practices. This book provides thorough coverage of the latest trends and best practices in Python development, equipping you with the tools to write clean, maintainable, and robust code. Through practical examples and hands-on exercises, you will learn how to apply ChatGPT in real-world scenarios, making your development process more efficient and productive. KEY FEATURES ● Supercharge the entire SDLC using ChatGPT's AI-driven insights. ● Seamlessly integrate ChatGPT into every stage of your Python projects. ● Practical, real-world examples and hands-on exercises. WHAT YOU WILL LEARN ● To seamlessly integrate ChatGPT from coding to deployment to monitoring. ● Use ChatGPT to gather and document software requirements. ● Break down features into stories with ChatGPT assistance. ● Design, architect, and implement clean, maintainable code using AI-generated snippets. ● Test, secure, and deploy applications with AI support. ● Optimize performance and monitor software using ChatGPT. WHO THIS BOOK IS FOR This book is for Python developers of all experience levels who want to enhance their entire software development process using AI. Basic knowledge of Python is assumed, but detailed instructions are provided to help you integrate ChatGPT into your projects effectively. TABLE OF CONTENTS 1. ChatGPT and Its Capabilities 2. Benefits of Using ChatGPT in Python Development 3. Setting up ChatGPT for Python Development 4. Requirements Gathering 5. Design and Architecture 6. Implementing a Software Product 7. Pull Review and Commit Messages 8. Using ChatGPT for Coding with SOLID Principles 9. Software Testing with ChatGPT in Python 10. Deployment with ChatGPT 11. Performance and Observability 12. Revolutionary Impact of ChatGPT 13. Limitations, Pitfalls and Dangers of ChatGPT 14. Preparing for the Future with ChatGPT