Jupyter notebooks demonstrating the creation of Neural Networks from scratch to classify MNIST handwritten digits using Python and SciPy.

This project involves implementing a Multilayer Perceptron (MLP) using the PyTorch library for MNIST-handwriting-digits dataset.

Repository contains my MATLAB files for the hand-coded MNIST (w/ SGD optimizer) classification model trained for the EEL5813 - Neural Networks: Algorithms and Applications course, PROJECT02

Developing a Handwritten Digits Classifier using PyTorch on the MNIST dataset .Implemented pytorch, CNN, image segmentation and classification

A resource-conscious neural network implementation for MCUs

Handwritten character recognition system that can recognize various handwritten characters or alphabets. I will extend this to recognize entire words or sentences.

Handwritten Digit Recognition using Python

MNIST handwritten digit classification, built with python/tensorflow, runs in browser

For the practical implementation of this project , i have created an app on Streamlit and uploaded on Streamlit Cloud Cloud

A classical-quantum or hybrid neural network with adversarial defense protection

Basic neural network model using Python and NumPy to recognize handwritten digits from the MNIST dataset.

An ML model trained on MNIST dataset to classify handwritten digits correctly.

This repository contains my coursework (assignments, semester exams & project) for the Statistical Machine Learning course at IIIT Delhi in Winter 2024.

A classical or convolutional neural network model with adversarial defense protection

My first Deep Learning Project

Real Time Digit Recognition using CNN model with keras.

A crude implementation of a image classifier on the MNIST dataset of handwritten digits

Deep-Learning-Optimization-Algorithms-Streamlit-Application

Classifier CNN and SelfAttentionCNN for MNIST handwritten digits (achieves 98% testing accuracy)

MNIST sandbox for CNN MLops course CS MSU 2023