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

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

Detects facial landmarks in real-time from the input feed of a webcam/usb-camera/pi-cam using a HOG + Linear SVM model.

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

Bag of Words Meets Bags of Popcorn

falppy-bird machine-learning program using svm and GAN

Vehicle detection using support vector classification and sliding windows

Experiments with several machine learning models for tumor classification

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

Handwritten digits recognition using logistic regression, Linear with PCA and LDA or dimensionality reduction and Kernel SVM, and Lenet-5 .

K-fold cross-validation implemented from scratch to aid in analysis of the MNIST dataset

FlairifyMe is a Reddit Flair Detector for r/india subreddit, that takes a post's URL as user input and predicts the flair for the post using a model generated by Logistic Regression.

Linear SVM, Quadratic SVM, SVM with RBF Kernel

This project focuses on classifying pulsar stars using the Support Vector Machine (SVM) algorithm, a powerful method in the realm of supervised learning. The goal is to automate the identification process of pulsar stars from candidates collected during surveys, based on predictive modeling.

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%.

A repository that contains practice code for ML algorithms implementation on a cancer treatment medical dataset from Kaggle (Text Processing, Response Encoding, Feature Engineering, Classification).

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