Handwritten Digit Recognition using Machine Learning and Deep Learning

Superpixel-based semantic segmentation, with object pose estimation and tracking. Provided as a ROS package.

Support Vector Machine in Javascript

🍃 Spam Classifier with Data Preparation and Support Vector Machine (SVM)

An undergraduate project to evaluate classifiers for facial expression recognition.

The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datasets, including Convolutional Neural Network (CNN).

EKG Analysis code for the MI3 intern group at CHOC Children's

My Implementation of Machine Learning models

Matlab/C++ library to evaluate SVM decision function and its derivatives.

Easy to understand classification problem from a highly skewed kaggle dataset. Solved using logistic regression and SVM, code inspired from top contributor.

Application of SVM classifier and NN classifiers for sentiment classification of Russian Twitter messages

Service for machine learning model prediction in Flask, celery

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

2018年全球程序员大赛参赛作品, 在给定的数据基础上,加上自己采集的飞机、天气等影响因子, 利用svm算法预测航班延误率.

Youtube Spam Comment Detector

PREDICT TUMOR IS MALIGNANT OR BENIGN

This repository contains projects from Andrew NG's Machine Learning course at Coursera

SVM model to classify SMS as spam or ham using Machine Learning

For conceptual understanding you can refer my medium blog which will provide you in-depth knowledge of SVC along with various other factors required in data science.

In this project, Based on dataset the breast cancer is classified with the help of Support Vector Machine.

Two Approaches to build a Machine Learning Classifier from scratch.

Using Stanford CoreNLP and SVM-Rank in a Supervised Approach to Text Difficulty Ranking

2019 [Julia] GPU CUDAnative SVM: a stochastic decomposition implementation of support-vector machine training

Thesis Research and Implementation

MachineLearning

In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity for their ability to perform well without any input hand-crafted features. Speech emotion on sets obtained from RAVDESS corpus is classified using a conventionally used Support Vector Machine (SVM) and its performance is compared to that of a bidirectional long short-term memory (LSTM).