Investigating the Behaviour of Deep Neural Networks for Classification

Experimented with different architectures and kernels on MNIST dataset using Convolutional Neural Networks.

Deep Learning Library

CS231n course assignment

Use NLP techniques to improve baseline model performance of a Question Answering problem

cifar10 classification based on alexnet and vgg16 using TensorFlow

CIFAR10 Dataset.

CS 182 Spring 2019 - Assignment 1

Implementation of Neural Network from scratch using Numpy. Contains implementation of foward & backward prop, Fully Connected Architectures, CNN, Batch Normalization, Activation functions, DataLoader, PatternProducingNetwork, multiple experiments with random parameter search, filter visualization, accuracy graph (on html), etc.

Training a model using CNN's to predict the emotion class of an Audio file in pytorch framework.

Building Deep Neural Network for Google Street View Dataset

Using DCGAN, detect and recognize house number from google street view

Denoising Diffusion Medical Model (DDMM) on PyTorch for generating datasets of Acute Lymphoblastic Leukemia 🩺💜

PyTorch implementation of batch normalization from "Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift" by Sergey Ioffe, Christian Szegedy

Deep Learning Course | Home Works | Spring 2021 | Dr. MohammadReza Mohammadi

in this repo, you will find implementation of various classification models, data augmantation ,cnn designing and model reguralization

A CNN model to identify images of plant seedlings.

Tune-Mode ConvBN Blocks For Efficient Transfer Learning