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Chapter 0: Fundamentals - ARENA

learn.arena.education · 769 words · saved by 1 readers

Please send any problems / bugs on the #errata channel in the Slack group, and ask any questions on the dedicated channels for this chapter of material. If you want to change to dark mode, you can do this by clicking the three horizontal lines in the top-right, then navigating to Settings → Theme. Links to all other chapters: (0) Fundamentals, (1) Transformer Interpretability, (2) RL. This section is designed to get you familiar with basic neural networks: how they are structured, the basic operations like linear layers and convolutions which go into making them, and why they work as well as they do. You'll start by making very simple neural networks, and by the end of today you'll build up to assembling ResNet34, a comparatively much more complicated architecture. For a lecture on the material today, which provides some high-level understanding before you dive into the material, watch the video below: In the first set of exercises, we'll cover the general structure of modules in PyTor

[0.2] - CNNs & ResNets Colab: exercises | solutions Please send any problems / bugs on the #errata channel in the Slack group , and ask any questions on the dedicated channels for this chapter of material. If you want to change to dark mode, you can do this by clicking the three horizontal lines in the top-right, then navigating to Settings → Theme. Links to all other chapters: (0) Fundamentals , (1) Transformer Interpretability , (2) RL . Introduction This section is designed to get you familiar with basic neural networks: how they are structured, the basic operations like linear layers and c

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