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This tutorial is part of my book "OpenAI GPT For Python Developers".
The goal of this book 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.
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.
We are excited to announce the imminent launch of Kala (AI/ML Weekly), the 13th newsletter in our series of developer-focused newsletters.
Deploying machine learning models into production requires selecting the right platform based on your needs. Managed cloud services provide end-to-end scaling while open source options offer flexibility. With proper preparation, your model can serve real-time, low-latency predictions at scale.