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 liorsinai.github.io
MicroGrad.jl: Part 1 ChainRules - Lior Sinai
| | bdtechtalks.com
A simple guide to gradient descent in machine learning - TechTalks
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| | Gradient descent is the main technique for training machine learning and deep learning models. Read all about it.
| | windowsontheory.org
Yet another backpropagation tutorial - Windows On Theory
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| | (Updated and expanded 12/17/2021) I am teaching deep learning this week in Harvard's CS 182 (Artificial Intelligence) course. As I'm preparing the back-propagation lecture, Preetum Nakkiran told me about Andrej Karpathy's awesome micrograd package which implements automatic differentiation for scalar variables in very few lines of code. I couldn't resist using this to show how...
| | matbesancon.xyz
Differentiating the discrete: Automatic Differentiation meets Integer Optimization |
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| | What can automated gradient computations bring to mathematical optimizers, what does it take to compute?
| | coornail.net
Teaching an AI to count
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| Neural networks are a powerful tool in machine learning that can be trained to perform a wide range of tasks, from image classification to natural language processing. In this blog post, well explore how to teach a neural network to add together two numbers. You can also think about this article as a tutorial for tensorflow.