🖼️ Text2Meme is a Meme Classification Experiment based on Caption Text (Implemented as a Discord Bot)
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Updated
Dec 8, 2022 - Jupyter Notebook
🖼️ 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
Cuisine Predictor is a python based tool which uses LinearSVC and kNeighborsClassifier to predict the cuisine and similar dishes from Yummly catlog.
A project on classification of GitHub readme sections using Machine Learning
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.
Spam Text Classifier / Penn State University
NLP analysis of ~200K AI news articles to identify impacted industries, companies, technologies, topics, and sentiment trends.
This project implements preprocessing, feature engineering, and multiple machine learning models to build a robust genre classification system.
Sentiment analysis of Yelp reviews using Apache Spark and machine learning models.
This is the material for Jose Portilla's Spark and Python for Big Data and ML course.
Trained and compared multiple ML models on a Kaggle thyroid cancer dataset. Tested class balancing and PCA to see how preprocessing affects each model.
5 Machine Learning Classifier trained and tested on streaming data folders ( to mimic real time data streaming ) using PySpark.
By Analyzing the dataset through Machine and Deep learning models we have to classify whether a person has heart disease or not.
This repository contains a Streamlit web app designed for fake news detection. Users can input a news article, and the app will predict whether it's real or fake based on its content. It also allows users to choose between different vectorizers (TF-IDF or Bag of Words) and classifiers (Linear SVM or Naive Bayes) to customize the prediction model.
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.
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