SVM app

This classifier predicts the genre of books based on titles or descriptions using a Machine Learning model trained on an Amazon books dataset.

SVM Implementation on make classfication datasets thats present in sklearn library,also apply hypermeter tuning

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

A Python interface to rusvm

YMood signal is a youtube comment sentiment analysis bot for helping advertisor to get more insight about content

Ruby language bindings for LIBSVM

IoT research project for user behavior prediction with mobile sensor data.

In this repository i performed a support vector classfication on real life data in order to make a machine learning classfication model , initially i performed some data preprocessing technique in order to filter out the data flaws then undergoes the process of model building i.e SVM Classification

This project implements a software defect prediction model using Support Vector Machine.

The "Diabetes Prediction" project focuses on predicting the likelihood of an individual having diabetes using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), and Support Vector Machines (SVM), this project offers a comprehensive solution for accurate classification.

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

Tugas Akhir mata kuliah "Metode Penelitian" dengan judul "Perbandingan Model CNN dan Model SVM untuk Mengidentifikasi Penyakit Daun Mangga"

This is a machine learning project made on Credit Card Fraud Detection. The data is taken from Kaggle. Different classification machine learning algorithms have been applied to get the maximum accuracy.

This project implements the Support Vector Machine (SVM) algorithm for predicting user purchase classification. The goal is to train an SVM classifier to predict whether a user will purchase a particular product or not.

Datamining concepts