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

♻️ Detection of Plastic Waste Type Based on Image Proccessing with Backpropagation Algorithm. The application that is built can detect the type of plastic waste including HDPE, LDPE, Other, PET, PP, PS, or PVC. The application can be used directly by accessing the dashboard or can be used on other platforms by utilizing the available RESTful API…

For Azimuth ACT course

Testing various examples and code for Machine Learning using TensorFlow

Assignments for the Machine Learning course (COL774) at IITD

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

Backpropogation algorithm implemented in Python 3

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)

The Deep Learning exercises provided in DataCamp

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

Implementation of a simple neural network with one hidden layer and training with backpropagation

Pytorch/ without Pytorch implementation of mnist handwriting dataset

Implementation of Logistic Regression considering a single Neural Network Node

This Jupyter Notebook contains a separate class of Neural Network.

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

All the assignments of DLFA course IIT KGP