Deep learning library in python from scratch
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Updated
Sep 8, 2022 - Python
Deep learning library in python from scratch
Unsupervised Deep Learning-based Pansharpening with Jointly-Enhanced Spectral and Spatial Fidelity
deep learning from scratch. uses numpy/cupy, trains in GPU, follows pytorch API
Implementation of feedforward-backpropagated Neural Network from Scratch
Neural Networks Fundamentals with Python – implementing neural networks from scratch
Let's build Neural Networks from scratch.
Learn to build neural networks from scratch, simply. No autograd, no deep learning libraries - just numpy.
XOR gate which predicts the output using Neural Network 🔥
Pure Python Simple Neural Network (SNN) library
PyTorch implementation of Neural Style Transfer
Code for my youtube video: Neural Network Crash Course, Ep 1
Implementing Neural Networks using Maths and Numpy only
Implementation of George Hotz's tinygrad.
Multilayer Neural Network from Scratch.
Open Source neural network framework/architecture
Neural Network from scratch without any machine learning libraries
PyTorch seq2seq implementation. Includes pretrained models for jokes<>punchlines and english<>french.
Basic feedforward neural network written from scratch in Python along with a manual explaining how to implement basic neural networks
A NumPy-based deep learning library for building neural networks. It features an automatic differentiation engine and supports training models like LSTM, CNN, and FNN.
A complete convolutional neural network implemented from scratch
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