first commit

LICENSE

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 MIT License
 
-Copyright (c) 2022 Andrej
+Copyright (c) 2022 Andrej Karpathy
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

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-# nn-zero-to-hero
-Neural Networks: Zero to Hero
+
+## Neural Networks: Zero to Hero
+
+A course of neural networks that starts all thew way at the basics. The course is a series of YouTube videos where we code and train neural networks together. The Jupyter notebooks we build in the videos are then captured here inside the [lectures](lectures/) directory. Every lecture also has a set of exercises included in the video description. (This may grow into something more respectable).
+
+---
+
+**Lecture 1: The spelled-out intro to neural networks and backpropagation: building micrograd**
+
+Backpropagation and training of neural networks. Assumes basic knowledge of Python and a vague recollection of calculus from high school.
+
+- [YouTube video lecture](https://www.youtube.com/watch?v=VMj-3S1tku0)
+- [Jupyter notebook files](lectures/micrograd)
+- [micrograd Github repo](https://github.com/karpathy/micrograd)
+
+---
+
+**Lecture 2: The spelled-out intro to language modeling: building makemore**
+
+We implement a bigram character-level language model, which we will further complexify in followup videos into a modern Transformer language model, like GPT. In this video, the focus is on (1) introducing torch.Tensor and its subtleties and use in efficiently evaluating neural networks and (2) the overall framework of language modeling that includes model training, sampling, and the evaluation of a loss (e.g. the negative log likelihood for classification).
+
+- [YouTube video lecture](https://www.youtube.com/watch?v=PaCmpygFfXo)
+- [Jupyter notebook files](lectures/makemore/makemore_part1_bigrams.ipynb)
+- [makemore Github repo](https://github.com/karpathy/makemore)
+
+---
+
+(ongoing...)
+
+---
+
+
+**License**
+
+MIT