Popular GitHub Repositories for Svm Classifier

Training SVM classifier to recognize people expressions (emotions) on Fer2013 dataset

基于Word2Vec+SVM对电商的评论数据进行情感分析

基于机器学习和OCR的车牌识别系统 @fujunhao

Predictive Maintenance System for Digital Factory Automation

AUTOMATED TYPE CLASSIFICATION OF GLAUCOMA DETECTION USING DEEP LEARNING

Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera

This work aims at using different machine learning techniques in detecting anomalies (including hardware failures, sabotage and cyber-attacks) in SCADA water infrastructure.

a robust AI library for detecting profanity in russian language (regex/SVM based), библиотека для детекции нецензурных слов в русском языке

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).

Implementing various machine learning algorithm from scratch

OpenTC is a text classification engine using several algorithms in machine learning

UpGrad Course workout for ML & AI

Authorship Attribution using CNNs

Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 on sarcasm detection are presented in this paper.

Emotion recognition system based on LBP-TOP.

Face Recognition and Classification Using FaceNet and MTCNN

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).

A chatbot developed to help FIB students. It uses NLP + Machine learning techniques such as sentence classification, or entity recognition (NER), along with a Deep Learning dialogue management model.

sentiment-analysis,document-classification,svm,logistic-regression,rcnn-text-classification, cnn-text-classification, lstm-text-classification, naive-bayes-classifier, sklearn-classify, pytorch

Improving News Classification Model Using Support Vector Machine and Naive Bayes