Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.
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Updated
Jul 3, 2024 - Jupyter Notebook
Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.
Get Started with Deep Learning
Implement neural networks from scratch with Micrograd. Learn derivatives, neurons, layers, and more through step-by-step Jupyter notebooks
Notes & Code to go over "Grokking Deep Learning" Book by Andrew Trask
Implementation notebooks and scripts of the Deep Learning Nanodegree Foundations program.
Backpropagation is a standard method for training a Neural Network. With this notebook, my attempt is to explain how it works with an explicit example.
Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
A python notebook
This repository contains Python notebook which contains creation of simple neural network. I have used synthesised 2 cluster dataset to train the network and test it.
Golang implementation of a single hidden layer feed forward neural network based on the Python notebook for Make Your Own Neural Network by Tariq Rashid
A set of autograd tutorial notebooks
Collection of notebooks I made on deep learning topics.
🍊 Intro to symbolic computation in Python including applications to function optimization, physics simulation and more. Includes notebooks on back-propagation, auto-diff and more.
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