Machine learning : modèles génératifs (GANs) avec PyTorch
Learn PyTorch by building a Generative Adversarial Network (GAN). Hands-on practice for deep learning enthusiasts.
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Explore the world of Generative AI! This topic covers foundational concepts, tools, and practical applications of Gen AI. Learn about text, image, and code generation. Discover how Gen AI is transforming various industries and its potential impact. Perfect for beginners curious about this rapidly evolving field.
Learn PyTorch by building a Generative Adversarial Network (GAN). Hands-on practice for deep learning enthusiasts.
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Generative AI creates new content like text, images, and code by learning patterns from existing data.
Common Generative AI models include GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and diffusion models.
While coding skills are helpful, many user-friendly platforms and APIs allow experimentation with Generative AI without extensive programming knowledge.
Generative AI uses machine learning algorithms to learn the underlying structure of training data and then generate new data points with similar characteristics.
Roles requiring Generative AI skills include AI engineers, prompt engineers, data scientists, and content creators who leverage AI tools for efficiency.