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.

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

A resource-conscious neural network implementation for MCUs

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

A calculator that uses handwritten digits and operators to calculate the result, using contour detection and CNN model prediction. Tensorflow (Keras) is used to create, train and load the neural network model used for predictions. CustomTKinter is used to provide the GUI. OpenCV and Pillow (PIL) are used for contour detection.

The goal of this project was to help me in learning more about neural networks and how ai and machine learning algorithms use deep learning.

A simple quick-start in performing digit recognition in a neural network in Keras.

different machine learning works on MNIST dataset

A sudoku solver application using machine learning

Personal Project to better my understanding of neural networks by writing one from scratch

本仓库包含了完整的深度学习应用开发流程，以经典的手写字符识别为例，基于LeNet网络构建。推理部分使用torch、onnxruntime以及openvino框架💖

a sample start to my deep learning journey

Our project builds a Convolutional Neural Network (CNN) model to accurately classify handwritten digits from the MNIST dataset. We preprocess the data and design a CNN architecture. Additionally, we create a user-friendly web interface using Flask for easy digit classification.