Cargando…

Modern generative AI with ChatGPT and OpenAI models : leverage the capabilities of OpenAI's LLM for productivity and innovation with GPT3 and GPT4 /

Generative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You'll start with an introduction to the fi...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Alto, Valentina (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing Ltd., 2023.
Edición:[First edition].
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

LEADER 00000cam a22000007i 4500
001 OR_on1380753617
003 OCoLC
005 20231017213018.0
006 m o d
007 cr cnu---unuuu
008 230531s2023 enka ob 001 0 eng d
040 |a ORMDA  |b eng  |e rda  |e pn  |c ORMDA  |d EBLCP  |d N$T  |d YDX  |d OCLCF  |d OCLCQ  |d QGK  |d IEEEE  |d OCLCO 
020 |a 9781805122838  |q electronic book 
020 |a 1805122835  |q electronic book 
020 |z 9781805123330 
029 1 |a AU@  |b 000074864542 
035 |a (OCoLC)1380753617 
037 |a 10251313  |b IEEE 
050 4 |a QA76.9.N38  |b A48 2023 
082 0 4 |a 006.3/5  |2 23/eng/20230613 
049 |a UAMI 
100 1 |a Alto, Valentina,  |e author. 
245 1 0 |a Modern generative AI with ChatGPT and OpenAI models :  |b leverage the capabilities of OpenAI's LLM for productivity and innovation with GPT3 and GPT4 /  |c Valentina Alto. 
250 |a [First edition]. 
264 1 |a Birmingham, UK :  |b Packt Publishing Ltd.,  |c 2023. 
300 |a 1 online resource (286 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
520 |a Generative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You'll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data. Next, you'll explore use cases where ChatGPT can boost productivity and enhance creativity. You'll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster. You'll also discover enterprise-level scenarios that leverage OpenAI models' APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you'll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications. By the end of this book, you'll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models' APIs in your own projects. 
588 0 |a Description based upon online resource; title from PDF title page (viewed June 12th, 2023). 
505 0 |a Cover -- Title Page -- Copyright and credits -- Contributors -- Table of Contents -- Preface -- Part 1: Fundamentals of Generative AI and GPT Models -- Chapter 1: Introduction to Generative AI -- Introducing generative AI -- Domains of generative AI -- Text generation -- Image generation -- Music generation -- Video generation -- The history and current status of research -- Summary -- References -- Chapter 2: OpenAI and ChatGPT -- Beyond the Market Hype -- Technical requirements -- What is OpenAI? -- An overview of OpenAI model families -- Road to ChatGPT: the math of the model behind it -- The structure of RNNs -- The main limitations of RNNs -- Overcoming limitations -- introducing transformers -- GPT-3 -- ChatGPT: the state of the art -- Summary -- References -- Part 2: ChatGPT in Action -- Chapter 3: Getting Familiar with ChatGPT -- Setting up a ChatGPT account -- Familiarizing yourself with the UI -- Organizing chats -- Summary -- References -- Chapter 4: Understanding Prompt Design -- What is a prompt and why is it important? -- Zero-, one-, and few-shot learning -- typical of transformers models -- Principles of well-defined prompts to obtain relevant and consistent results -- Avoiding the risk of hidden bias and taking into account ethical considerations in ChatGPT -- Summary -- References -- Chapter 5: Boosting Day-to-Day Productivity with ChatGPT -- Technical requirements -- ChatGPT as a daily assistant -- Generating text -- Improving writing skills and translation -- Quick information retrieval and competitive intelligence -- Summary -- Chapter 6: Developing the Future with ChatGPT -- Why ChatGPT for developers? -- Generating, optimizing, and debugging code -- Generating documentation and code explainability -- Understanding ML model interpretability -- Translation among different programming languages -- Summary. 
505 8 |a Chapter 7: Mastering Marketing with ChatGPT -- Technical requirements -- Marketers' need for ChatGPT -- New product development and the go-to-market strategy -- A/B testing for marketing comparison -- Boosting Search Engine Optimization (SEO) -- Sentiment analysis to improve quality and increase customer satisfaction -- Summary -- Chapter 8: Research Reinvented with ChatGPT -- Researchers' need for ChatGPT -- Brainstorming literature for your study -- Providing support for the design and framework of your experiment -- Generating and formatting a bibliography -- Generating a presentation of the study -- Summary -- References -- Part 3: OpenAI for Enterprises -- Chapter 9: OpenAI and ChatGPT for Enterprises -- Introducing Azure OpenAI -- Technical requirements -- OpenAI and Microsoft for enterprise-level AI -- introducing Azure OpenAI -- Microsoft AI background -- Azure OpenAI Service -- Exploring Playground -- Why introduce a public cloud? -- Understanding responsible AI -- Microsoft's journey toward responsible AI -- Azure OpenAI and responsible AI -- Summary -- References -- Chapter 10: Trending Use Cases for Enterprises -- Technical requirements -- How Azure OpenAI is being used in enterprises -- Contract analyzer and generator -- Identifying key clauses -- Analyzing language -- Flagging potential issues -- Providing contract templates -- Frontend with Streamlit -- Understanding call center analytics -- Parameter extraction -- Sentiment analysis -- Classification of customers' requests -- Implementing the frontend with Streamlit -- Exploring semantic search -- Document embedding using LangChain modules -- Creating a frontend for Streamlit -- Summary -- References -- Chapter 11: Epilogue and Final Thoughts -- Recap of what we have learned so far -- This is just the beginning -- The advent of multimodal large language models. 
505 8 |a Microsoft Bing and the Copilot system -- The impact of generative technologies on industries -- a disruptive force -- Unveiling concerns about Generative AI -- Elon Musk calls for stopping development -- ChatGPT was banned in Italy by the Italian "Garante della Privacy" -- Ethical implications of Generative AI and why we need Responsible AI -- What to expect in the near future -- Summary -- References -- Index -- Other Books You May Enjoy. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
630 0 0 |a ChatGPT. 
650 0 |a Natural language processing (Computer science) 
650 0 |a Artificial intelligence  |x Computer programs. 
650 6 |a Traitement automatique des langues naturelles. 
650 6 |a Intelligence artificielle  |x Logiciels. 
650 7 |a Artificial intelligence  |x Computer programs  |2 fast 
650 7 |a Natural language processing (Computer science)  |2 fast 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781805123330/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL30587006 
938 |a EBSCOhost  |b EBSC  |n 3619025 
994 |a 92  |b IZTAP