[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes

A reinforcement learning model specialized in stock prediction utilizing deep learning techniques, incorporating reward mechanisms, compatible with any machine equipped with Python.

Extremely fast evaluation of the extrinsic clustering measures: various (mean) F1 measures and Omega Index (Fuzzy Adjusted Rand Index) for the multi-resolution clustering with overlaps/covers, standard NMI, clusters labeling

Resampling Tools for Time Series Forecasting with Modeltime

Generalized Conventional Mutual Information (GenConvMI) - NMI for overlapping (soft, fuzzy) clusters (communities), compatible with standard NMI, pure C++ version (single executable)

Implementation of SVM Classifier To Perform Classification on the dataset of Breast Cancer Wisconin; to predict if the tumor is cancer or not.

Landscape of ML/DL performance evaluation metrics

End-to-end implementation of Spam Detection in Email using Machine Learning, Python, Flask, Gunicorn, Scikit-Learn, and Logistic Regression on the Heroku cloud application platform.

No description provided.

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidates more likely to have the visa certified.

This Model is used to Predict Emails data. Either emails are Spam or Normal (Ham) Mail.

Compute the metric of text recognition algorithm.

This project aims to understand and build Naive Bayes classifier to predict the salary of a person.

Sinhala text extraction, preprocessing, and classification considering subject and domain.

A fast, modern Chess Review Engine ♟️ built with FastAPI + React. Analyzes PGNs using Stockfish, classifies moves (Brilliant → Blunder), shows top moves, accuracy, and clean interactive insights ⚡📊 You can even download a Brilliant-move image 🤩 Similar to chess.com review — but free and completely Open-Source 🔥

Scrapped tweets using twitter API (for keyword ‘Netflix’) on an AWS EC2 instance, ingested data into S3 via kinesis firehose. Used Spark ML on databricks to build a pipeline for sentiment classification model and Athena & QuickSight to build a dashboard

Deep Learning Face Detection and Verification

To Detect Sepsis Disease using six Classifiers on clinical data

The project is an integral cog in Computer Vision and Artificial Intelligence and Machine learning. It aims to determine the activity of a human from a video provided to the machine. It is a step forward in solving various problems like surveillance, fall detection for elderly or sick people, robotics and computer interaction, security among many others. We want a higher accuracy in doing so with respect to the videos used for training the machine.

Supervised Machine Learning project with KNN, decision tree, random forest and adaboost algorithms

Developed a Convolutional Neural Network based on VGG16 architecture to diagnose COVID-19 and classify chest X-rays of patients suffering from COVID-19, Ground Glass Opacity and Viral Pneumonia. This repository contains the link to the dataset, python code for visualizing the obtained data and developing the model using Keras API.

Classification Metric Manager is metrics calculator for machine learning classification quality such as Precision, Recall, F-score, etc.

Applying K Means and KNN on a multiclass dataset to make clusters and find nearest neighbours.

ABCRaster stands for Accuracy assessment of Binary Classified Raster. It is a package for performing validation, accuracy assessment, or comparing binary classified rasters (.tiff) versus a reference (.shp). Primary use case is to compare flood maps encoded as (1,0) in tiff file format against a reference vector from CEMS.

Multiple Object Tracking in video Using Deep learning

A simple Python model that uses TFIDF Vectorizer and Passive Agressive Classifier to detect fake and irrelevant news

To Detect Early Sepsis Disease

Big Data Project - SSML - Spark Streaming for Machine Learning

A machine learning model for spam mail prediction classifies incoming emails as either "spam" or "not spam" (ham) based on the content and other features.

A set of python scripts for spatially explicit accuracy assessments of binary, gridded geospatial data, e.g., for human settlement data mapping built-up (1) and not built-up (0) areas.