🖼️ Text2Meme is a Meme Classification Experiment based on Caption Text (Implemented as a Discord Bot)
-
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
Cuisine Predictor is a python based tool which uses LinearSVC and kNeighborsClassifier to predict the cuisine and similar dishes from Yummly catlog.
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 on classification of GitHub readme sections using Machine Learning
Hate speech detection — YouTube comment classifier (TF-IDF + LinearSVC, 78.5% accuracy) + AI polite chatroom moderator.
A project to predict if customer churns or not using ML algorithms
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.
Trained and compared multiple ML models on a Kaggle thyroid cancer dataset. Tested class balancing and PCA to see how preprocessing affects each model.
This is the material for Jose Portilla's Spark and Python for Big Data and ML course.
Sentiment analysis of Yelp reviews using Apache Spark and machine learning models.
5 Machine Learning Classifier trained and tested on streaming data folders ( to mimic real time data streaming ) using PySpark.
Predicting Police Attendance on Road Accidents
This project implements preprocessing, feature engineering, and multiple machine learning models to build a robust genre classification system.
Have build a predictive model to determine the likelihood of survival for passengers on the Titanic using data science techniques in Python.
Multi-Label Classifier with ETL, NLP, Sklearn, Flask, + Plotly
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.
Add a description, image, and links to the linear-svc topic page so that developers can more easily learn about it.
To associate your repository with the linear-svc topic, visit your repo's landing page and select "manage topics."