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Jan 6, 2024 · I like to train Deep Neural Nets on large datasets. - karpathy
karpathy / nn-zero-to-hero Public. Notifications. Fork 1.2k. Star 10.4k. master. README. MIT license. Neural Networks: Zero to Hero. A course on neural networks that starts all the way at the basics. The course is a series of YouTube videos where we code and train neural networks together.
Jan 20, 2018 · Describing a new pet project that tracks active windows and keystroke frequencies over the duration of a day (on Ubuntu/OSX) and creates pretty HTML visualizations of the data. This allows me to gain nice insights into my productivity. Code on Github. Jul 3, 2014 Feature Learning Escapades
karpathy / llama2.c Public. Notifications. Fork 1.8k. Star 16k. master. README. MIT license. llama2.c. Have you ever wanted to inference a baby Llama 2 model in pure C? No? Well, now you can! Train the Llama 2 LLM architecture in PyTorch then inference it with one simple 700-line C file ( run.c ).
May 7, 2022 · Andrej karpathy. I like to train Deep Neural Nets on large datasets. 53.7k followers · 7 following. Stanford. https://twitter.com/karpathy. karpathy / README .md. I like deep neural nets. Pinned. nanoGPT Public. The simplest, fastest repository for training/finetuning medium-sized GPTs. Python 23.7k 3.1k. micrograd Public.
Neural Networks: Zero to Hero. A course by Andrej Karpathy on building neural networks, from scratch, in code. We start with the basics of backpropagation and build up to modern deep neural networks, like GPT.
Chapter 1: Real-valued Circuits. In my opinion, the best way to think of Neural Networks is as real-valued circuits, where real values (instead of boolean values {0,1}) “flow” along edges and interact in gates. However, instead of gates such as AND, OR, NOT, etc, we have binary gates such as * (multiply), + (add), max or unary gates such as ...
