This project implements a basic neural network using C++ for classification tasks. The network is designed to handle a spiral dataset and includes components for forward and backward propagation, as well as optimization.

American Sign Language (ASL) Detection using CNN

Github repo for ML Specialization course on Coursera. Contains notes and practice python notebooks.

Python from-scratch implementation of a Neural Network Classifier

Open-source AI library (audio to text, simple NLP, and common algorithms)

The purpose of this project is to develop a machine learning model that predicts employee attrition (whether an employee will leave the company) and department assignment (which department an employee belongs to) based on various factors. These factors include age, travel frequency, education level, job satisfaction, marital status, and more.

This AI "Plant Doctor" uses image analysis to diagnose plant diseases. It learns from the PlantVillage dataset and employs powerful techniques

Study of the impact of a Randomized ReLU function on the performance of a neural network model.

A multi-task deep learning model that solves multiple tasks concurrently. Specifically, the model is designed to be effective in multiple contexts (e.g., classification, segmentation, regression) simultaneously.

Project inspired by a book titled, "Artificial Intelligence," by Copeland. One of the World's first Quantum Neural Networks ever invented.

This project is a deep learning model built with PyTorch that classifies images into two categories: cats and dogs.

QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch

Get Started with Deep Learning

"A TensorFlow-based neural network model for classifying handwritten digits from the MNIST dataset."

learning python day 11

Here, we will provide a PyTorch regime to handle the partial differential equation solution of the heat equation by executing Deep Kolmogorov Method of Beck et. al.

Implementations of neural networks in python for the classification of MNIST datasets.

Neural-Net-Numpy(NNN) is a simple python package for training neural networks using only numpy components

First task in course

"The 'Activation Functions' project repository contains implementations of various activation functions commonly used in neural networks. "