What do you think?
Rate this book
OpenAI GPT For Python Developers: The art and science of developing intelligent apps with OpenAI GPT-3, DALL·E 2, CLIP, and Whisper - Suitable for learners of all levels
Explore the fascinating world of Artificial Intelligence and solve real-world problems!In this practical guide, you will build intelligent real-world applications using GPT-3, DALL-E, Whisper, CLIP, and more tools from the OpenAI and AI/ML ecosystem.Rest assured, you don't need to be a data scientist or machine learning engineer to follow this guide. It was designed in a way that suits a programmer with a basic/intermediate level.The knowledge you gain from this guide will be applicable to GPT-3 and will likely also be relevant to GPT-4, 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.
The goal is to provide a step-by-step guide to using GPT-3 in your projects through this API but not only - many other tools and models built by OpenAI such as Whisper (an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data), CLIP (Contrastive Language-Image Pre-Training), a neural network trained on a variety of (image, text) pairs and DALL·E 2, a new AI system that can create realistic images and art from a description in natural language.
Whether you’re building a chatbot, an AI (voice) assistant, a semantic search engine, a classification system, a recommendation engine a web app providing AI-generated data, or any other sort of natural language/image/voice processing and generation platform, this guide will help you reach your goals.
The explanations in this book are crystal clear and easy to understand, employing simple Python code, examples, and hands-on exercises.
This guide is focused on practical, hands-on learning and is designed to help the reader build real-world applications. The guide is example-driven and provides a lot of practical examples to help the reader 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 built applications such
A fine-tuned medical chatbot assistantAn intelligent coffee recommendation systemAn intelligent conversational system with memory and contextAn AI voice assistant like Alexa but smarterA Chatbot assistant to help with Linux commandsA semantic search engineA news category prediction systemAn image recognition intelligent systemAn image generatorThis guide helps
Understand different models and when to use themGenerate human-like text for various purposesControl creativity and generate high-quality textTransform and edit text for useful tasksOptimize GPT models' performanceStem, lemmatize, and reduce bills when using the APIPractice advanced techniques like Context Stuffing and chainingLearn how Tesla and Notion use text embeddingImplement semantic search and other advanced toolsCreate prediction algorithms and zero-shot techniques and evaluate accuracyPractice and improve few-sho
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.
The goal is to provide a step-by-step guide to using GPT-3 in your projects through this API but not only - many other tools and models built by OpenAI such as Whisper (an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data), CLIP (Contrastive Language-Image Pre-Training), a neural network trained on a variety of (image, text) pairs and DALL·E 2, a new AI system that can create realistic images and art from a description in natural language.
Whether you’re building a chatbot, an AI (voice) assistant, a semantic search engine, a classification system, a recommendation engine a web app providing AI-generated data, or any other sort of natural language/image/voice processing and generation platform, this guide will help you reach your goals.
The explanations in this book are crystal clear and easy to understand, employing simple Python code, examples, and hands-on exercises.
This guide is focused on practical, hands-on learning and is designed to help the reader build real-world applications. The guide is example-driven and provides a lot of practical examples to help the reader 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 built applications such
A fine-tuned medical chatbot assistantAn intelligent coffee recommendation systemAn intelligent conversational system with memory and contextAn AI voice assistant like Alexa but smarterA Chatbot assistant to help with Linux commandsA semantic search engineA news category prediction systemAn image recognition intelligent systemAn image generatorThis guide helps
Understand different models and when to use themGenerate human-like text for various purposesControl creativity and generate high-quality textTransform and edit text for useful tasksOptimize GPT models' performanceStem, lemmatize, and reduce bills when using the APIPractice advanced techniques like Context Stuffing and chainingLearn how Tesla and Notion use text embeddingImplement semantic search and other advanced toolsCreate prediction algorithms and zero-shot techniques and evaluate accuracyPractice and improve few-sho
378 pages, Kindle Edition
Published May 3, 2023
5 people are currently reading
9 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
No one has reviewed this book yet.