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 ML ecosystem.
Rest assured, you don't need to be a data scientist or machine learning engineer to follow this guide.
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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 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 more tools!
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.
If you have the basics of Python programming language and are open to learning a few more techniques like using Pandas Dataframes and some NLP techniques, you have all the necessary tools to start building intelligent systems using OpenAI tools.
Rest assured, you don't need to possess the title of a data scientist, machine learning engineer, or AI expert to comprehend the concepts, techniques, and tutorials presented in this guide. Our explanations 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 as:
By reading this guide and following the examples, you will be able to:
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 ML ecosystem. Rest assured, you don't need to be a data scientist or machine learning engineer to follow this guide.
Aymen El Amri