linear-svc

🖼️ Text2Meme is a Meme Classification Experiment based on Caption Text (Implemented as a Discord Bot)

AI Biceps Curl Counter

DiagnoX is an open source project dedicated to diagnosing rare diseases. The original code is designed and specialized towards

Building machine learning classifiers to label tweets as "Hate Speech", "Offensive Language", or "Neither"

A project to predict if customer churns or not using ML algorithms

A project on classification of GitHub readme sections using Machine Learning

Cuisine Predictor is a python based tool which uses LinearSVC and kNeighborsClassifier to predict the cuisine and similar dishes from Yummly catlog.

There are three classes InfoTheory, CompVis and Math. These can occur in any combination, so an article could be all three at once, two, one or none. The job is to build text classifiers that predict each of these three classes individually using the Abstract field.

This is the material for Jose Portilla's Spark and Python for Big Data and ML course.

Spam Text Classifier / Penn State University

5 Machine Learning Classifier trained and tested on streaming data folders ( to mimic real time data streaming ) using PySpark.

Sentiment analysis of Yelp reviews using Apache Spark and machine learning models.

This project implements preprocessing, feature engineering, and multiple machine learning models to build a robust genre classification system.

Trained and compared multiple ML models on a Kaggle thyroid cancer dataset. Tested class balancing and PCA to see how preprocessing affects each model.

An intent-based conversational AI and recommendation engine for the Steam game catalog.

NLP analysis of ~200K AI news articles to identify impacted industries, companies, technologies, topics, and sentiment trends.

Credit scoring is a crucial task in financial institutions to assess the creditworthiness of individuals or businesses. This project focuses on building classification models to predict credit scores based on various features such as income, debt, and credit history.

Build a machine learning pipeline using the MLEnd Yummy Dataset to classify images as containing rice or chips, leveraging LinearSVC and advanced image processing techniques for accurate food identification.