Resource scheduling and cluster management for AI

A dataset of 29843 cat pictures (64x64), compiled together for training models.

A full-stack Machine Learning web application for generating synthetic epidemiological data, training multiple ML models, and predicting disease outbreak risk through an interactive dashboard.

Auto driving car simulation using neural networks and model training. Used html canvas for draw elements and javascript for train the model. not any third party libraries used.

Fast & Lightweight Model Training Platform

BrainVision AI is a fully client-side brain tumor classifier that runs entirely in the browser using ONNX Runtime Web. It processes MRI images locally, preserving privacy while delivering fast and reliable predictions. The project includes a responsive UI, multi-language support, theme switching, and a complete training pipeline with Keras and ONNX

Learn the basics of neural networks by training a model on XOR and AND operations

This repository is created for learning purposes and contains code adapted from a course. It serves as a reference for my personal learning journey. For the original repository and resources, please check out .https://github.com/charliegerard/fem-ml-workshop

A curated collection of machine learning projects covering data preprocessing, model training, evaluation, and experimentation workflows.

🧠 Classify brain tumors in your browser with BrainVision AI — a fast, privacy-focused tool using client-side machine learning for accurate diagnostics.

This group project aims to predict the fatality of an accident given a certain input (time/weather condition/etc.) using machine learning models and Flask.

This project is a prototype for image recognition based attendance system

[NVIDIA ONLY] Optimized Training script for Ace-Step with low VRAM support for local GPUs. (Requirements 8GB VRAM)