A machine learning project to predict NCAA Men's Basketball outcomes
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Updated
Dec 8, 2022 - Python
A machine learning project to predict NCAA Men's Basketball outcomes
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
Plot tree based machine learning models
CLI tool for testing Office documents with macros using MaliciousMacroBot
Stock Price Prediction using Random Forest
This project aims to tackle this problem by developing a system that can effectively detect fake news using machine learning techniques.
This repository contains a Flask application for detecting phishing URLs using machine learning. It includes preprocessing, feature extraction, model training, and model deployment in a web application.
Classification of various products into different categories is a very important task. Doing this classification, one can get various types of insights about the specific product. This also helps in doing product matching when you try and search a product on a eCommerce site.
Detecting phishing website using machine learning
Code release for "Flood Extent Mapping During Hurricane Florence With Repeat-Pass L-Band UAVSAR Images"
Syndrome Prediction Helps to predict the disease through analysing group of symptoms
🔍 Discover the future of healthcare with our Lung Cancer Detection Project. Using advanced machine learning techniques, we've achieved 92% accuracy in identifying lung cancer. Join us at the forefront of medical AI. 👩⚕️🌟 #AIHealthcare #LungCancerDetection
Using spark streaming, predicts the violation location in real time for New York parking tickets dataset
Efficient Android Malware detection using Random - Protype of BA's final project (Efficient Android Malware Detection using RL) - Amit Moshe (@Amit223) & Inbar Roth (@Inbaroth) & Liad Bercovich (@liadber)
Stacking Classifier with parallel computing architecture based on Message Passing Interface.
This was a group project where we are comparing the effectiveness of supervised learning using various multivariate data sets and i was involved doing so using Random Forest Model. I implemented the feature importance of various predictor variables and how it effects the error rate(RMSE). I used the Student Performance Dataset to show the import…
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