Developing Apps with GPT-4 and ChatGPT : Build Intelligent Chatbots, Content Generators, and More

Olivier Caelen

ISBN 10: 1098168100 / ISBN 13: 9781098168100

Editore: O'reilly Media Sep 2024, 2024

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Neuware - This book provides an ideal guide for Python developers who want to learn how to build applications with large language models. Authors Olivier Caelen and Marie-Alice Blete cover the main features and benefits of GPT-4 and GPT-3.5 models and explain how they work. You'll also get a step-by-step guide for developing applications using the OpenAI Python library, including text generation, Q&A, and smart assistants.

Codice articolo 9781098168100

Dati bibliografici

• Titolo: Developing Apps with GPT-4 and ChatGPT : Build Intelligent Chatbots, Content Generators, and More
• Editore: O'reilly Media Sep 2024
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 1098168100
• ISBN 13: 9781098168100
• Rilegatura: Taschenbuch
• Edizione: seconda edizione
• Condizione: Neu
• Dimensioni: 229 L x 174 A x 15 P (millimetri) 229 millimetri di larghezza per 174 millimetri di altezza per 15 millimetri di profondità
• Peso: 482 grammi

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Riassunto

This book provides an ideal guide for Python developers who want to learn how to build applications with large language models. Authors Olivier Caelen and Marie-Alice Blete cover the main features and benefits of GPT-4 and GPT-3.5 models and explain how they work. You'll also get a step-by-step guide for developing applications using the OpenAI Python library, including text generation, Q&A, and smart assistants.

Written in clear and concise language, Developing Apps with GPT-4 and ChatGPT includes easy-to-follow examples to help you understand and apply the concepts to your projects. Python code examples are available in a GitHub repository, and the book includes a glossary of key terms. Ready to harness the power of large language models in your applications? This book is a must.

You'll learn:

• Fundamentals and benefits of GPT-4 and GPT-3.5 models, including the main features and how they work
• How to integrate these models into Python-based applications, leveraging natural language processing capabilities and overcoming specific LLM-related challenges
• Examples of applications demonstrating the OpenAI API in Python for tasks including text generation, question answering, content summarization, classification, and more
• Advanced LLM topics such as prompt engineering, fine-tuning models for specific tasks, RAG, plug-ins, LangChain, LlamaIndex, GPTs, and assistants

Olivier Caelen is a machine learning researcher at Worldline and teaches machine learning courses at the University of Brussels.

Marie-Alice Blete, a software architect and data engineer in Worldline's R&D department, is interested in performance and latency issues associated with AI solutions.