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neural-network-from-scratch

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This repository contains the collection of explorative notebooks pure in python and in the language that we, humans can read. Have tried to compile all lectures from the Andrej Karpathy's 💎 playlist on Neural Networks - which we will end up with building GPT.

  • Updated Apr 30, 2024
  • Jupyter Notebook
Little-NeuralNetwork-Library

My first simple realization of Neural Network library by scratch, so you can use it in your projects (check the documentation in README). You can see an example how to use the library below.

  • Updated Aug 29, 2020
  • C#

Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21

  • Updated May 2, 2021
  • Python

This is the code for a fully connected neural network. The code is written from scratch using Numpy, without using any ready-made deep learning library. In this, classification is done on the MNIST dataset. It is generalized to include various options for activation functions, loss functions, types of regularization, and output activation types.

  • Updated Jun 14, 2024
  • Jupyter Notebook

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