This repository contains codes in python to categorize images from CIFAR-10 data set by using Convolutional Neural Network (CNN)

Using neural network binary classification to predict if donations to organizations are successful.

Various applications of deep learning have been demonstrated.

This project involves the use of classical neural networks for the computation of the heat equation with Neumann boundary conditions and a gaussian distribution as initial condition.

Image classification of handwritten numbers in MNIST dataset.

Image Classification, Python, Feedforward-Neural-Network, Tensorflow, Keras, CNN, ReLu

Spring 2024: CS5720: Neural Network Deep Learning: In Class Programming Assignment-6

An artificial neural network used for distinguishing between signal and continuum B events in Belle II monte carlo based on event topology. Competition submission for Belle II CNN competition, placed 5th with 95% efficiency.

Text Generation

Deep Learning with python

Comparison of ReLU

Predicting if a patient is diabetic or not by training a classification model using both Logistic regression and Artificial neural networks

Building CNN(Convolutional Neural Network) model

💡Implementing a custom Maxout network from scratch (as an extension of nn.Module in Pytorch) and testing model performance on MNIST in comparison to ReLU networks to determine whether Maxout's more complex function approximations can provide higher accuracies in real-world use cases.

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

Backward pass of ReLU activation function for a neural network.

Create manually a Neural Network model to predict unicode chars

Breast Cancer Detection using Deep Neural Network: In these project I worked on sklearn datasets and predicted "Malignant" or "Benign" on breast cancer dataset with 94% Accuracy.

This repository summarizes the basic concepts, types and usage scenarios of activation functions in deep learning.