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

Corpus and a baseline neural network system for Named Entity Recognition in Hindi-English Code-Mixed social media text.

Boundary F1 Score - Python Implementation

Image key points Extraction, Description, Feature Matching

Verifying suitability of dysphonia measurements for diagnosis of Parkinson’s Disease using multiple supervised learning algorithms.

Detecting drug-drug interaction (DDI) has become a vital part of public health safety. This project is an implementation of NLP based approach for such relation extraction between entities.

Automatic method for the recognition of hand gestures for the categorization of vowels and numbers in Colombian sign language based on Neural Networks (Perceptrons), Support Vector Machine and K-Nearest Neighbor for classifier /// Método automático para el reconocimiento de gestos de mano para la categorización de vocales y números en lenguaje d…

Script for calculating the optimal cut-off for max. F1-score, etc.

Better multi-class confusion matrix plots for Scikit-Learn, incorporating per-class and overall evaluation measures.

A hyperopt wrapper - simplifying hyperparameter tuning with Scikit-learn style estimators.

A comprehensive command-line tool for analyzing Formula 1 race data using the FastF1 library.

Semantic F1 Score: Fair Evaluation Under Fuzzy Class Boundaries

This is a web based elective course recommender system implemented with flask and Sklearn

Contributed to a vision-driven accessibility tool translating sign language into text

🤟 Enhance sign language interpretation using transfer learning and multimodal features for accurate gesture recognition and robust evaluation methods.

Predict sales prices and practice feature engineering, RFs, and gradient boosting

A modern PyTorch implementation of hierarchical deep temporal models for group activity recognition

Clasificación de url con RandomForestClassifier

Implements and evaluates TrieHH and SFP heavy-hitter algorithms under local differential privacy, including full data preprocessing, simulation, and F1-score analysis on Wikipedia Clickstream. Designed for reproducible experiments and privacy–utility benchmarking.

Text Classification Problem : Wrote a module to classify Amazon-Product Reviews as favourable/unfavourable. Achieved accuracy of 78% and an F1 score of .81 using Logistic Regression on a test-train split of 20%, where total records were around 50000.