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4.25
172 valoraciones

Generative AI - From Big Picture, to Idea, to Implementation

How the next milestone in machine learning will improve the products we build
Instructor
Martin Musiol
947 Estudiantes inscritos
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Recently, we have seen a shift in AI that wasn’t very obvious. Generative Artificial Intelligence (GAI) – the part of AI that can generate all kinds of data – started to yield acceptable results, getting better and better. As GAI models get better, questions arise e.g. what will be possible with GAI models? Or, how to utilize data generation for your own projects?

In this course, we answer these and more questions as best as possible.

There are 3 angles that we take: 

  1. Application angle: we get to know many GAI application fields, where we then ideate what further projects could emerge from that. Ultimately, we point to good starting points and how to get GAI models implemented effectively.

    The application list is down below.

  2. Tech angle: we see what GAI models exist. We will focus on only relevant parts of the code and not on administrative code that won’t be accurate a year from now (it’s one google away). Further, there will be an excursion: from computation graphs, to neural networks, to deep neural networks, to convolutional neural networks (the basis for image and video generation).

    The architecture list is down below.

  3. Ethical angle/ Ethical AI: we discuss the concerns of GAI models and what companies and governments do to prevent further harm.

Enjoy your GAI journey!

List of discussed application fields:

  • Cybersecurity 2.0 (Adversarial Attack vs. Defense)

  • 3D Object Generation

  • Text-to-Image Translation

  • Video-to-Video Translation

  • Superresolution

  • Interactive Image Generation

  • Face Generation

  • Generative Art

  • Data Compression with GANs

  • Domain-Transfer (i.e. Style-Transfer, Sketch-to-Image, Segmentation-to-Image)

  • Crypto, Blockchain, NFTs

  • Idea Generator

  • Automatic Video Generation and Video Prediction

  • Text Generation, NLP Models (incl. Coding Suggestions like Co-Pilot)

  • GAI Outlook

  • etc.

Generative AI Architectures/ Models that we cover in the course (at least conceptually):

  • (Vanilla) GAN

  • AutoEncoder

  • Variational AutoEncoder

  • Style-GAN

  • conditional GAN

  • 3D-GAN

  • GauGAN

  • DC-GAN

  • CycleGAN

  • GPT-3

  • Progressive GAN

  • BiGAN

  • GameGAN

  • BigGAN

  • Pix2Vox

  • WGAN

  • StackGAN

  • etc.

También puedes estudiar
The implementation of a simple GAN
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Generative AI - From Big Picture, to Idea, to Implementation
4.25
172 valoraciones
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Vídeo 6 horas
Certificado de finalización
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Acceso en el móvil y en la televisión