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In this video I cover Flax - a JAX-based machine learning library. It's a part of my machine learning with JAX series of videos! You'll learn everything you need to get you started building ML models in Flax.

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✅ Flax notebook (do follow along!): https://github.com/gordicaleksa/get-s...
✅ Flax GitHub: https://github.com/google/flax
✅ Flax docs: https://flax.readthedocs.io/en/latest/
✅ HuggingFace Flax community week: https://github.com/huggingface/transf...
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⌚️ Timetable:
00:00:00 Intro - Flax is performant and reproducible
00:02:00 Deepnote walk-through (sponsored)
00:04:57 Flax basics
00:14:05 Flax vs Haiku
00:17:25 Benchmarking Flax
00:18:28 Linear regression toy example
00:27:05 Introducing Optax (Adam state example)
00:33:15 Creating custom models
00:39:30 self.param example
00:45:55 self.variable example
00:57:15 Handling dropout, BatchNorm, etc.
01:02:25 CNN on MNIST example
01:11:00 TrainState source code
01:13:00 CNN dropout modification
01:15:05 Outro and summary

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Huge thank you to these AI Epiphany patreons:
Eli Mahler
Petar Veličković

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#flax #jax #deeplearning