Developing Apps with GPT-4 and ChatGPT Build Intelligent Chatbots, Content Generators, and More
Original price was: $11.23.$10.99Current price is: $10.99.
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| L | 38-40 | 12-14 | 37-39 | 30-32 | 39-41 | |
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| Youth | XS | 128 | 7 | 26-28 | 23-24 | 26-28 |
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| L | 146 | 12 | 32-34 | 26-27 | 32-34 | |
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| Men | 28 | 44 | 28 | 28 | 34 | 30 |
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| 7 | 39 | 6.5 | 9.5 | |
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| 9 | 41 | 8.5 | 10.25 | |
| 10 | 42 | 9.5 | 10.625 | |
| 11 | 43 | 10.5 | 11 | |
| 12 | 44 | 11.5 | 11.25 |
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.
