A curated list of project tutorials for project-based learning.
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Updated
Nov 3, 2024 - TypeScript
scikit-learn is a widely-used Python module for classic machine learning. It is built on top of SciPy.
A curated list of project tutorials for project-based learning.
Powerful machine learning library for Node.js – uses Python's scikit-learn under the hood.
🧠 An open-source machine learning application for analyzing software defect reports extracted from bug tracking systems.
Open source Cloud Framework for exposing scalable Machine-Learning-as-a-Service implementation
This Netflix Recommendation System is a web application developed using Node.js and Express. It utilizes a recommendation engine written in Python
Deploying a machine learning model to Heroku.
A distributed ledger-based blockchain implementation of the rates proposed and charged, and the commodity count by hospitals for treatment and consultancy of patients.
Agrologer is an integrated platform designed to assist farmers in managing water-related issues, offering real-time data analysis and remote monitoring capabilities.
Estate AI is a machine learning application that predicts the approximate rent a user would need to pay for their requirement across major metro cities of India. It is built using NextJS 13, TailwindCSS, and TypeScript for the frontend, Scikit Learn for Model Training and and Flask for the backend.
A platform for reading personalized research articles from different platforms.
Uncover originality, empower authenticity
🐱 An image classification ML project, with an interactive website, and a deployed model
The Verifier DApp is an application that generates and trades verified carbon credits, using blockchain technology, IoT, and AI to process images of trees and analyze environmental data, aiding in the quantification of forest biomass and the generation of carbon credits.
Web version of Greenient
Created a prediction model to predict a players points per game (PPG) stat for the upcoming 2024-2025 season based on their PPG from the past 3 seasons (2022-2022, 2022-2023, 2023-2024). Used a Linear Regression model using sklearn to combine a player's data from all three seasons to help predict their PPG in the upcoming 2024-2025 season.
This project is a collaborative effort by a team of six to create an Online Employee Management System.
Monte Carlo Fantasy Football Draft Simulator Featuring FastAPI, NextUI, and ODMantic
EcoSphere is a Generative AI-powered platform designed to help users plan eco-friendly events with ease.
Machine Learinig Model uses a personalized approach to provide recommendations based on health data entered by users, such as age, weight, height, and lifestyle habits.
Created by David Cournapeau
Released January 05, 2010
Latest release 2 months ago