"This program trains a model using 'SVM' or 'Softmax' and predicts the input data. Loss history and predicted tags are displayed as results."

Smelling bugs with an Electronic Nose

Ruby language bindings for LIBSVM

Custom implementation of Support Vector Machines using Python and NumPy

baby cry analysis to identify the reason behind baby's cry

Gender recognition system based on Support Vector Machine (SVM) and machine learning

This a very simple SVM Spam Emails Classification problem, I used Sklearn library to train the model and get better results

Implemented SVM classifier, visualized decision boundary, performed a unit test to verify functionality

Reducing the Number of Training Samples for Fast Support Vector Machine Classification python implementation

The dataset is about past loans. The loan_train.csv data set includes details of 346 customers whose loans are already paid off or defaulted.

What is the relationship between airline sentiments and airlines? What is the reason for the negativity mentioned in the dataset? What is the relation of time with sentiments? Which model is best for sentiment analysis when we do ensemble learning?

A web application to see effect of C hyperparameter on classification boundary and marginal threshold in SVM.

Twitter sentiment analysis allows you to keep track of what's being said about your product or service on social media, and can help you detect angry customers or negative mentions before they they escalate.

Detection of Tomato leaf various diseases using SVM and Neural networks.

No-reference Stereoscopic Image Quality Predictor using Deep Features from Cyclopean Image

To see if drivers were being profiled. I built a Support Vector Machine (SVM) classifier and a randomForest classifier to predict a driver's race given the traffic's stop's details. Successful classification will indicate the existence of bais in the traffic stops' data.

A model I used (breast cancer dataset) to teach myself SVMs and learning more Scikit-learn w/ notes

We will be creating an algorithmic crypto trading bot that will use the Kraken API to get crypto prices. We will use machine learning to determine the trend of the market from historical data and determine the best strategies/indicators to use.

A collaborative project looking into the likelihood of Covid-19 infection in the United States.