Potato Disease Classification - Training, Rest APIs, and Frontend to test.

FEDn: An enterprise-ready open source federated learning framework. This repository contains the Python framework, CLI and API.

ML Nexus is an open-source collection of machine learning projects, covering topics like neural networks, computer vision, and NLP. Whether you're a beginner or expert, contribute, collaborate, and grow together in the world of AI. Join us to shape the future of machine learning!

Asteroid Feature Prediction Machine Learning Models

Deep learning Projects with code

Detection of Plant diseases and classifying into respective categories

DNN model for correcting biases in satellite-derived SST data

OrthoSeg makes it easy to train neural networks to segment orthophotos.

how to implement Transfer Learning using the pre-trained ResNet50 model to classify different types of flowers

This Python code allows you to generate dream-like images inspired by a text prompt and a base image.

Machine Learning - Projects (Supervised Learning, Unsupervised, Deep Learning, NLP)

Project to detect nepali barnamala

Simple Logistic Regression and Neural Network powered Machine Learning models that predicts whether a breast tumor is malignant or benign based on input features extracted from a breast cancer dataset.

🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱

"🎨🤖 Doodle-Guesser Game: Draw doodles & let AI guess! Powered by a CNN trained on Google's QuickDraw dataset (1 million+ images and 345 classes), it predicts in real-time and shows the top 5 probabilities with a pie chart 🥧. Built using TensorFlow, Keras, & Streamlit. A fun blend of AI & gaming! 🚀"

🤖 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning techniques and pre-trained models to accurately identify and categorize images based on their respective classes. Also includes a sample Flask backend!

This repository shows all of my Jupyter Notebook or Google CoLab projects. Through the Promoting Inclusivity in Computing program at San Francisco State, I have learned many coding skills. These include, Interdisciplinary Python Biological Applications, Data Structures, and now Machine Learning.

A deep learning-based project to classify kidney diseases.

The Plant Disease Classification project uses the NasNetMobile deep learning model to classify plant conditions into five categories: fungus, healthy, virus, pests , and bacteria . With a FastAPI backend, SQL Server database, and Streamlit frontend, it enables users to upload images and get quick, accurate disease predictions.