Explore live open-source projects and AI models.

Analysis of Air Pollution prediction and time-series forecast of PM2.5 Pollutant using Machine Learning Algorithms (SVM, Decision Tree and Random Forest) and Deep Learning Algorithms (CNN, Bi-LSTM). Also considered for improved performances is random search hyper-parameter tuning using Ray-Tune w... Read more

Applied various machine learning algorithms like KNN regressor, Support Vector Machine regresson, Linear, Polynomial, Ridge and Lasso regressions. Identified best model using Grid Search. Calculated accuracy of the models using cross validation and predicted bitcoin prices using the best model.

AI Resume Screening is a tool that uses artificial intelligence to automate the process of resume screening and shortlisting. The tool uses natural language processing and machine learning algorithms to analyze resumes and classify them to the job roles based on the words in their resume.

AeroSense Analytics is a machine learning–powered air quality prediction and classification system designed to assess environmental conditions with high accuracy. The project uses advanced data preprocessing, feature engineering, and multiple supervised learning algorithms to predict and classif... Read more

A comparative analysis of 4 ML algorithms. This Hypertension Risk Prediction Model can be described as a machine learning model designed to predict an individual's risk of developing hypertension based on various input parameters.

An rigorous, well documented machine learning analysis pipeline for binary classification datasets assembled as a Jupyter Notebook. Includes exploratory analysis, data processing, feature processing, ML modeling (9 algorithms, including the original ExSTraCS algorithm) with hyperparameter sweeps,... Read more

I employ an advanced approach combining Google Earth Engine (GEE) and data from the MODIS satellite to gather comprehensive remote sensing data. This data is then analyzed using cutting-edge Machine Learning Algorithms, specifically XGBoost and Random Forest (RF), to accurately predict crop yield... Read more

💧 Inland water systems are essential to our environment because they are vital ecosystems that are bio-diverse. Thus, finding innovative ways to monitor water quality is vital. In this repository, I present various machine learning algorithms that takes in multispectral remote sensing data from t... Read more

For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming bugs is a time consuming task. Major part of bug triaging is the assignment of a bug report to a developer with the appropriate expertise, who can resolve/fix the bug without reassigning to so... Read more

Predict if the client will subscribe to direct marketing campaign for a banking institution Problem Statement: The data is related to direct marketing campaigns of a Portuguese banking institution. Predict if the client will subscribe to a term deposit based on a marketing campaign-Data Set Downl... Read more