backpropogation

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

A trainable convolutional neural network inside a fragment shader

An implementation of various metaheuristics adapted to train neural networks

For Azimuth ACT course

a scale-free network of applied and foundational AI resources

A multi-layer, feedforward neural network (FNN) implementation in Java

Creating a basic NN from scratch to detect numbers from the MNIST dataset using Numpy

Testing various examples and code for Machine Learning using TensorFlow

Assignments for the Machine Learning course (COL774) at IITD

This Repository contains the lab Programs for On-Going Soft Computing Lab (CSP 3035) Summer 2025

Backpropogation algorithm implemented in Python 3

The Deep Learning exercises provided in DataCamp

This gradient decent library has not only a determination function, but it has emotions too, as an add on! (Currently the emotions are anger, surprise and excitement)(By emotions, I JUST MEAN BUILT-IN FUNCTIONS FOR EFFICIENT TRAINING)

Built from scratch neural network library using only NumPy

Multivariate Classification Using a Feed-Forward Neural Network and Backpropagation.

A NumPy-only Multilayer Perceptron (MLP) built from first principles to demystify neural networks, backpropagation, and optimization algorithms.

All the assignments of DLFA course IIT KGP

A Selection of Artificial Sudoku Solvers

Course work from UCLA's ECE C247 - Neural Networks