neual-network

The official code implement of [ SIGMOD25 Demo | KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection]

This repository contains the deep learning model used to predict pedestrian crossing behavior, developed as a final project of the Computer Vision course (academic year 23/24).

Hand Post detection model by using neural network and draw ponits with html canvas

A game in which the player would lead its follower and compete with other groups. The last surviving group would win the game.

Embark on an introductory course on computational intelligence, covering topics like unsupervised learning, decision trees, SVM, perceptron, MLP, CNN, NLP, and ensemble classifiers. 🤖📚💡 Designed for TA-led classes at Ferdowsi University of Mashhad (FUM). Start your machine learning journey! 🚀

App with CNN neural network to diagnose different fractures on x-ray pictures

A PyTorch implementation of pipeline parallelism strategies for training large neural networks across multiple GPUs/devices.

Neural Networks and Deep Learning Projects

A complete, hands-on Deep Learning course with PyTorch — from tensors to deployment

A basic feedforward neural network implemented in C, with SDL2 for visualization. This project aims to build a neural network from scratch, focusing on core concepts like backpropagation and gradient descent.

che3le: ANN python library implementation from scratch using object-oriented programming principles

A PyTorch-based neural network for classifying segmented numeric images. This project demonstrates a custom architecture and training loop for multi-segment image inputs, including experiments with optimizers, batch sizes, and learning rates.

This repository contains the Assignments and Projects of Deep Learning Specialization Course on Coursera.

This project implements a deep learning–based image classification system for automated garbage classification. The model categorizes waste into different classes to support efficient waste management, recycling processes, and environmental sustainability initiatives.

Training and Testing Different Models on Mushrooms and Telecoms Dataset

Partial Domain Adaptation (PDA) is a domain adaptation scenario where the target domain's label space is a subset of the source domain's label space

React application to demonstrate how convolutional neual networks can be used to identify simple drawings

Discover the Handwritten Digit Recognition! 🚀 Unleash the power of neural networks with this code snippet, as it delves into the world of AI-driven Handwritten Digit Recognition. The celebrated MNIST dataset serves as the foundation, guiding the process of building, training, and evaluating models for precise digit predictions.

Image Classifier using 6 different types of Convolutional Neural Networks with end-to-end pipeline and deployment using Github Actions