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🎨 From Zero to Generative: Learning generative modelling from scratch

Welcome to the wild world of generative models :) Buckle up, because we're about to move from "What's a neural network?" to "I trained a flow matching generative model using convolutional neural networks" in only two steps.

The slides for the lecture accompanying this tutorial can be found here.

🧠 What's in store?

  1. Classify: Build your first image classifier
  2. Generate: Train your first generative model for images

💡 No prior ML knowledge required! But be warned: this journey might be challenging. If you find yourself stuck, remember: it's not you, it's the notebook! 😉

🎢 The Road Ahead

These notebooks are your trusty guidebook through the land of JAX and generative models. You'll laugh, you'll cry, you'll write code that sometimes works! Here's what to expect:

  • Frustration: It's part of the learning process. Embrace it!
  • Eureka moments: They're coming, we promise!
  • Fun: Enjoy the journey :)

🆘 Need Help?

  • Solutions: Available in the solutions branch of the GitHub repo. But resist the temptation! Use only in cases of extreme frustration or impending nervous breakdown.
  • Teaching Assistants: They're not just sleeping on zoom looking pretty. Ask them questions! They feed on your curiosity.

Ready to dive in? Click on Open in Colab and let's start our generative journey! 🏊‍♂️

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