Openai Gpt For Python Developers 2nd Edition

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Openai Gpt For Python Developers 2nd Edition

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Author : Aymen El Amri
language : en
Publisher: Independently Published
Release Date : 2024-02-14

Openai Gpt For Python Developers 2nd Edition written by Aymen El Amri and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-14 with Computers categories.

The knowledge you'll acquire from this guide will be applicable to the current families of GPT models (GPT-3, GPT-3.5, GPT-4, etc.) and will likely also be relevant to GPT-5, should it ever be released. OpenAI provides APIs (Application Programming Interfaces) to access their AI. The goal of an API is to abstract the underlying models by creating a universal interface for all versions, allowing users to use GPT regardless of its version. This guide aims to provide a comprehensive, step-by-step tutorial on how to utilize GPT-3.5 and GPT-4 in your projects via this API. It also covers other models, such as Whisper and Text-to-Speech. If you're developing a chatbot, an AI assistant, or a web application that utilizes AI-generated data, this guide will assist you in achieving your objectives. If you have a basic understanding of the Python programming language and are willing to learn a few additional techniques, such as using Pandas Dataframes and some NLP methods, you possess all the necessary tools to start building intelligent systems with OpenAI tools. Rest assured, you don't need to be a data scientist, machine learning engineer, or AI expert to comprehend and implement the concepts, techniques, and tutorials presented in this guide. The explanations provided are straightforward and easy to understand, featuring simple Python code, examples, and hands-on exercises. This guide emphasizes practical, hands-on learning and is designed to assist readers in building real-world applications. It is example-driven and provides numerous practical examples to help readers understand the concepts and apply them to real-life scenarios to solve real-world problems. By the end of your learning journey, you will have developed applications such as: Fine-tuned, domain-specific chatbots. An intelligent conversational system with memory and context. A semantic modern search engine using RAG and other techniques. An intelligent coffee recommendation system based on your taste. A chatbot assistant to assist with Linux commands A fine-tuned news category prediction system. An AI-to-AI autonomous discussion system to simulate human-like conversations or solve problems An AI-based mental health coach trained on a large dataset of mental health conversations and more! By reading this guide and following the examples, you will be able to: Understand the different models available, and how and when to use each one. Generate human-like text for various purposes, such as answering questions, creating content, and other creative uses. Control the creativity of GPT models and adopt the best practices to generate high-quality text. Transform and edit the text to perform translation, formatting, and other useful tasks. Optimize the performance of GPT models using various parameters and options such as max_tokens, temperature, top_p, n, stream, logprobs, stop, presence_penalty, frequency_penalty, best_of, and others. Stem, lemmatize and reduce your costs when using the API. Understand Context Stuffing, chaining, and practice prompt engineering. Implement a chatbot with memory and context. Create prediction algorithms and zero-shot techniques and evaluate their accuracy. Understand, practice, and improve few-shot learning. Understand fine-tuning and leverage its power to create your own fine-tuned models. Understand and use fine-tuning best practices Practice training and classification techniques using GPT. Understand embedding and how companies such as Tesla and Notion are using it. Understand and implement semantic search, RAG, and other advanced tools and concepts. Integrate a Vector Database (e.g.: Weaviate) with your intelligent systems.

Openai Gpt For Python Developers

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Author : Aymen El Amri
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-21

Openai Gpt For Python Developers written by Aymen El Amri and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-21 with Technology & Engineering categories.

"OpenAI GPT for Python Developers" is your comprehensive guide to mastering the integration of OpenAI's GPT models into your Python projects, enhancing applications with various AI capabilities from chat completions to AI avatars. Key Features Strategies for optimizing and personalizing GPT models for specific applications. Insights into integrating additional OpenAI technologies like Whisper and Weaviate. Strong emphasis on responsible AI development and deployment. Book Description“OpenAI GPT for Python Developers” is meticulously crafted to provide Python developers with a deep dive into the mechanics and applications of GPT technology, beginning with a captivating narrative on the evolution of OpenAI and the fundamental workings of GPT models. As readers progress, they will be expertly guided through the essential steps of setting up a development environment tailored for AI innovations, coupled with insightful advice on selecting the most appropriate GPT model to suit specific project needs. The guide progresses into practical tutorials that cover the implementation of chat completions and the art of prompt engineering, providing a solid foundation in harnessing the capabilities of GPT for generating human-like text responses. Practical applications are further expanded with discussions on the creation of autonomous AI-to-AI dialogues, the development of AI avatars, and the strategic use of AI in interactive applications. In addition to technical skills, this book addresses the ethical implications and prospects of AI technologies, encouraging a holistic view of AI development. The guide is enriched with detailed examples, step-by-step tutorials, and comprehensive explanations that illuminate the theoretical aspects and emphasize practical implementation.What you will learn Set up the development environment for OpenAI GPT. Understand and choose the right GPT model for your needs. Implement advanced prompt engineering techniques. Explore embedding and advanced embedding examples. Utilize OpenAI's Whisper for speech recognition and translation. Integrate OpenAI TTS models for text-to-speech applications. Who this book is for This book is designed for readers at an intermediate to advanced level who have a basic understanding of machine learning concepts and are eager to expand their expertise in AI with a focus on OpenAI's technologies. Ideal for those involved in AI-driven projects, the book assumes familiarity with Python programming and a fundamental grasp of AI principles. It’s especially beneficial for developers aiming to integrate GPT models into applications, AI researchers, and technical professionals involved in AI product development.

Ai And Machine Learning For Coders

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Author : Laurence Moroney
language : en
Publisher: O'Reilly Media
Release Date : 2020-10-01

Ai And Machine Learning For Coders written by Laurence Moroney and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-01 with Computers categories.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving

Exploring Gpt 3

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Author : Steve Tingiris
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-08-27

Exploring Gpt 3 written by Steve Tingiris and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-27 with Computers categories.

Get started with GPT-3 and the OpenAI API for natural language processing using JavaScript and Python Key FeaturesUnderstand the power of potential GPT-3 language models and the risks involvedExplore core GPT-3 use cases such as text generation, classification, and semantic search using engaging examplesPlan and prepare a GPT-3 application for the OpenAI review process required for publishing a live applicationBook Description Generative Pre-trained Transformer 3 (GPT-3) is a highly advanced language model from OpenAI that can generate written text that is virtually indistinguishable from text written by humans. Whether you have a technical or non-technical background, this book will help you understand and start working with GPT-3 and the OpenAI API. If you want to get hands-on with leveraging artificial intelligence for natural language processing (NLP) tasks, this easy-to-follow book will help you get started. Beginning with a high-level introduction to NLP and GPT-3, the book takes you through practical examples that show how to leverage the OpenAI API and GPT-3 for text generation, classification, and semantic search. You'll explore the capabilities of the OpenAI API and GPT-3 and find out which NLP use cases GPT-3 is best suited for. You'll also learn how to use the API and optimize requests for the best possible results. With examples focusing on the OpenAI Playground and easy-to-follow JavaScript and Python code samples, the book illustrates the possible applications of GPT-3 in production. By the end of this book, you'll understand the best use cases for GPT-3 and how to integrate the OpenAI API in your applications for a wide array of NLP tasks. What you will learnUnderstand what GPT-3 is and how it can be used for various NLP tasksGet a high-level introduction to GPT-3 and the OpenAI APIImplement JavaScript and Python code examples that call the OpenAI APIStructure GPT-3 prompts and options to get the best possible resultsSelect the right GPT-3 engine or model to optimize for speed and cost-efficiencyFind out which use cases would not be suitable for GPT-3Create a GPT-3-powered knowledge base application that follows OpenAI guidelinesWho this book is for Exploring GPT-3 is for anyone interested in natural language processing or learning GPT-3 with or without a technical background. Developers, product managers, entrepreneurs, and hobbyists looking to get to grips with NLP, AI, and GPT-3 will find this book useful. Basic computer skills are all you need to get the most out of this book.

Transformers For Natural Language Processing

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Author : Denis Rothman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-01-29

Transformers For Natural Language Processing written by Denis Rothman and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-29 with Computers categories.

Publisher's Note: A new edition of this book is out now that includes working with GPT-3 and comparing the results with other models. It includes even more use cases, such as casual language analysis and computer vision tasks, as well as an introduction to OpenAI's Codex. Key FeaturesBuild and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning modelsGo through hands-on applications in Python using Google Colaboratory Notebooks with nothing to install on a local machineTest transformer models on advanced use casesBook Description The transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains with transformers. The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face. The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets. What you will learnUse the latest pretrained transformer modelsGrasp the workings of the original Transformer, GPT-2, BERT, T5, and other transformer modelsCreate language understanding Python programs using concepts that outperform classical deep learning modelsUse a variety of NLP platforms, including Hugging Face, Trax, and AllenNLPApply Python, TensorFlow, and Keras programs to sentiment analysis, text summarization, speech recognition, machine translations, and moreMeasure the productivity of key transformers to define their scope, potential, and limits in productionWho this book is for Since the book does not teach basic programming, you must be familiar with neural networks, Python, PyTorch, and TensorFlow in order to learn their implementation with Transformers. Readers who can benefit the most from this book include experienced deep learning & NLP practitioners and data analysts & data scientists who want to process the increasing amounts of language-driven data.

Beginning Chatgpt For Python

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Author : Lydia Evelyn
language : en
Publisher: Springer Nature
Release Date : 2024-11-22

Beginning Chatgpt For Python written by Lydia Evelyn and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-22 with Computers categories.

Unlock the future of software development and empower yourself to elevate your Python applications by harnessing the power of AI as this field continues to grow and evolve. Perfect for beginner to intermediate Python programmers, this book breaks down the essentials of using ChatGPT and OpenAI APIs. You'll start with the basics, learning to authenticate, send prompts, generate responses, test in the Playground, and handle errors with ease. Each chapter includes hands-on exercises that bring concepts to life, demonstrating different API functionalities and practical applications. You'll master models like GPT-4o, GPT-4, GPT-3.5, Whisper, and DALL-E, enabling you to enhance your applications with cutting-edge AI. Discover how generative AI tools like ChatGPT can automate tedious tasks rather than replace jobs. Leverage ChatGPT’s powerful Natural Language Processing (NLP) capabilities to handle various formats of unstructured text within your Python apps. Quickly see how easy it is to use ChatGPT as your AI-pair programmer, boosting your productivity and speed. This step-by-step guide will have you creating intelligent chatbots that can automatically process messages from Slack or Discord. With Beginning ChatGPT for Python, you'll master the ChatGPT and OpenAI APIs, building intelligent applications that offer a personalized and engaging user experience. What You’ll Learn Connect with the ChatGPT and OpenAI APIs and send effective prompts. Harness parameters like temperature and top_p to create unique and engaging responses from ChatGPT. Create an intelligent assistant bot for Slack that automates tasks and enhances productivity. Develop a bot that can moderate conversations and manage communities on Discord. Add context to your prompts to get more accurate and relevant responses. Who This Book Is For Python developers and enthusiasts who aspire to employ OpenAI and ChatGPT in the creation of intelligent applications to enhance productivity.

Social Data Analytics In The Cloud With Ai

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Author : Xuebin Wei
language : en
Publisher: CRC Press
Release Date : 2024-12-30

Social Data Analytics In The Cloud With Ai written by Xuebin Wei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Technology & Engineering categories.

The rise of cloud computing and Generative artificial intelligence (AI) has revolutionized data analytics pipelines. Analysts can collect, store, and process vast datasets in the cloud with high availability and scalability, and also leverage Generative AI to query and visualize datasets in natural languages. This pioneering textbook provides a gateway for students, educators, and professionals to develop and enhance social data analytics capabilities with the latest cloud computing and AI technologies. The textbook introduces educational cloud resources from leading technology companies, begins with foundational concepts, and progresses to advanced techniques. Features The first textbook on cloud-based social data analytics with the assistance of Generative AI. Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB. Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization. Analyzes Census and social media data with the latest large language models (LLMs). Provides hands-on exercises with real-world datasets on timely issues. This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.

Deep Learning For Coders With Fastai And Pytorch

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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29

Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Developing Apps With Gpt 4 And Chatgpt

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Author : Olivier Caelen
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-07-10

Developing Apps With Gpt 4 And Chatgpt written by Olivier Caelen and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-10 with Computers categories.

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.

Code Complete 2nd Edition

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Author : Steve Mcconnell
language : en
Publisher:
Release Date :

Code Complete 2nd Edition written by Steve Mcconnell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.

Widely considered one of the best practical guides to programming, Steve McConnell s original CODE COMPLETE has been helping developers write better software for more than a decade. Now this classic book has been fully updated and revised with leading-edge practices-and hundreds of new code samples-illustrating the art and science of software construction. Capturing the body of knowledge available from research, academia, and everyday commercial practice, McConnell synthesizes the most effective techniques and must-know principles into clear, pragmatic guidance. No matter what your experience level, development environment, or project size, this book will inform and stimulate your thinking-and help you build the highest quality code.