A fast, robust Python library to check for offensive language in strings.

A cluster of Machine Learning algorithms

Detecting hate speech using the spoken content of videos using Machine Learning

Tour of Machine Learning Algorithms for Binary/Multiclass Classification

Wrapper on top of liblinear-tools

Android malware detection from static features with ML classification algorithms- Decision Tree, K-Nearest Neighbours, Linear SVM and Random Forest.

Using deep learning and transfer learning techniques to differentiate plain roads and those with potholes using three different classifiers to obtain the best accuracy with the same convolutional base

Forest cover type classification/detection using linear support vector machine implemented with gradient descent (from scratch)

SMS spam detection pipeline: dual TF-IDF (word+char) → calibrated Linear SVM, nested CV + threshold tuning (F1) + explainability + robustness tests.

Twitter Sentiment Analysis (Ml hackathon)

Semantic Enrichment, Data Augmentation and Deep Learning for Boosting Invoice Text Classification Performance: A Novel Natural Language Processing Strategy

Face detection using Facial Landmark prediction and Comparision of standard emotion recognition algorithms

Syracuse University, Masters of Applied Data Science - IST 736 Text Mining

🧠 TumorClassifier-RAW-vs-DIP – an advanced 🔬 medical imaging platform 🏥 with 🤖 AI-powered brain tumor classification 🧬 (MRI analysis 📊), 🔄 image preprocessing pipeline (RAW vs DIP comparison 📈), ⚡ Linear SVM classifier 🎯 for tumor detection, 📊 performance metrics visualization 📉, interactive web 🌐 interface for real-time predictions.

Package provides javascript implementation of support vector machines

Performed feature selection using F-score method to filter out the important features in order to optimize the performance of Linear SVM machine learning model. The accuracy achieved was above 63%.

This repository demonstrates a complete machine learning workflow for banknote authentication using a hand coded Linear SVM model. It includes data preparation, training loop design, vectorized computation of gradients, model metrics, and a visualization module based on two selected features.

No description provided.

Prediction of diabetes health indicators for machine learning class final project

Statistical Pattern Recognition (classic machine learning)

Iris Species Classification usin various ML models.

This project used OpenCV HOG people detector to build an accurate and fast enough implementation to detect people in images and videos.

Detect different parts of the face such as, eyes brows, nose, jaw, etc. individually

Bag of Words Meets Bags of Popcorn

No description provided.

Implementation of Perceptron, Winnow and Adagrad-Perceptron, along with their averaged versions on synthetic and real world datasets

Practice from My Machine Learning Certificate from Cornell

Data Science Project (Clustering + SVM)

Twitter sentiment analysis using machine learning, classifying tweets into Positive, Negative, Neutral, or Irrelevant.

mirror of https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/ranksvm/liblinear-ranksvm-2.11.zip