Example of Machine Learning application: State of Charge estimation of a battery using SVR
-
Updated
Nov 19, 2019 - Python
Example of Machine Learning application: State of Charge estimation of a battery using SVR
An undergraduate project to evaluate classifiers for facial expression recognition.
AgriAid is an AI-powered tool for farmers & agricultural agents in Bangladesh, offering plant disease forecasting & identification. Using machine learning, deep learning & Python, it helps increase crop yield & food security.
Animates the SVM Decision Boundary Hyperplane on the Iris data
PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM
Using Stanford CoreNLP and SVM-Rank in a Supervised Approach to Text Difficulty Ranking
Throtale is a Automated API throttling system (Rate-limiting) open source project it will predict dynamically the rate limit at particular time periods.
Signature Verification using Deep Convolution Neural Networks
Reducing the Number of Training Samples for Fast Support Vector Machine Classification python implementation
Contains code involving CS 503 - Lab 3 : Implementation of Support vector Machine.
This project implements a software defect prediction model using Support Vector Machine.
This a very simple SVM Spam Emails Classification problem, I used Sklearn library to train the model and get better results
Predicting the stance for tweets using SVM
This project demonstrates the application of Support Vector Machines. 📚
YMood signal is a youtube comment sentiment analysis bot for helping advertisor to get more insight about content
Using scikit-learn and mlxtend
In this project Simple handwritten digit recognizer is created using python
This is a SVM(Support Vector Machine) for Machine Learning.
Add a description, image, and links to the svm-training topic page so that developers can more easily learn about it.
To associate your repository with the svm-training topic, visit your repo's landing page and select "manage topics."