Focusing on Sentiment Analysis .

A website visualising various classification algorithms

SVM module

This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.

Masters Thesis

a support vector based machine learning to predict the tolerance rates in the bacterial infections. It uses eps-regression and although the c-type classification can be applied if you want to predict the time variable

Repository for University of Michigan Ross School of Business Independent Research.

Value or Momentum? Comparing Random Forests, Support Vector Machines, and Multi-layer Perceptrons for Financial Time Series Prediction & Tactical Asset Allocation

Credit card fraud detection from credit card transactions using machine learning.

ML based Smart Crop Recommendation System with Disease Identification, utilizing CNNs. It aids farmers in selecting crops, managing diseases, and boosts productivity by integrating weather and geolocation APIs.

Comparative analysis of various Machine Learning Classification algorithms on the diabetic prediction dataset.

Machine Learning Engineering Spring 2024 Project

This project employs machine learning for early autism detection. Utilizing Python and SVM, it offers two models: one trained on a verified dataset for classification, and another for real-time prediction from user input, enhanced with visualizations for insightful analysis.

A curated list of Best Artificial Intelligence Resources

30 Semi-Supervised Learning Algorithms

A model that makes use of SVM, Logistic Regression, Naive Bayes to judge whether a review is positive or negative

Protego browser extension captures URL and analyze it using machine learning model trained with Random Forest and Support Vector Machine.

Cognifyz Technologies Data Science Internship project on Restaurant Data Analysis to explore insights and build predictive models.

Analyzed customer churn using transaction data. Built ML model to predict lapses. Dataset includes customer status, collection/redemption info, and program tenure. Delivered business presentation outlining modeling approach, findings, and churn reduction strategies.

This project focuses on developing machine learning models for predicting the presence of diabetes using the logistic regression, support vector machine (SVM) and KNeighborsClassifier algorithms.