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micrograd
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
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Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
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For autograd from scratch, see https://github.com/karpathy/micrograd and/or
https://windowsontheory.org/2020/11/03/yet-another-backpropa...
Interesting find. Just FYI, this repo has been the OG for several years, when it comes to building NN from scratch:
https://github.com/eriklindernoren/ML-From-Scratch
For those interested in simple neural networks to CNN and RNNs implemented with just Numpy (including backprop):
https://github.com/parasdahal/deepnet
Nice! I made a gpu accelerated backpropagation lib a while ago to learn about NNs, if you are interested check it out here: https://github.com/zbendefy/machine.academy
I found Andrew Ng’s Deep Learning Specialization much better for understanding neural networks than the machine learning course. https://www.coursera.org/specializations/deep-learning
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