Popular GitHub Repositories for Support Vector Machines

(CGCSTCD'2017) An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations. CGCSTCD = China Graduate Contest on Smart-city Technology and Creative Design

Simple machine learning library / 簡單易用的機器學習套件

Python Machine Learning Algorithms

Today, using machine learning algorithms is as easy as "import knn from ..." but it doesn't really help if you want to learn how the algorithms work

A C++ toolkit for Convex Optimization (Logistic Loss, SVM, SVR, Least Squares etc.), Convex Optimization algorithms (LBFGS, TRON, SGD, AdsGrad, CG, Nesterov etc.) and Classifiers/Regressors (Logistic Regression, SVMs, Least Squares Regression etc.)

Implementation of a paper in q/KDB+ and python - "Forecasting ETFs with Machine Learning Algorithms" - Jim Kyung-Soo Liew and Boris Mayster

# Machine Learning (Coursera) This is my solution to all the programming assignments and quizzes of Machine-Learning (Coursera) taught by Andrew Ng. After completing this course you will get a broad idea of Machine learning algorithms. Try to solve all the assignments by yourself first, but if you get stuck somewhere then feel free to browse the code. ## Contents * Lectures Slides * Solution to programming assignment * Solution to Quizzes by Andrew Ng, Stanford University, [Coursera](https://www.coursera.org/learn/machine-learning/home/welcome) ### Week 1 - [X] Videos: Introduction - [X] Quiz: Introduction - [X] Videos: Linear Regression with One Variable - [X] Quiz: Linear Regression with One Variable ### Week 2 - [X] Videos: Linear Regression with Multiple Variables - [X] Quiz: Linear Regression with Multiple Variables - [X] Videos

Spam filtering module with Machine Learning using SVM (Support Vector Machines).

detect objects using svm and opencv

Predicting emotions based on speech audio samples of American English, German and British English languages using Support Vector Machine, K-Nearest Neighbor, Random Forest and Recurrent Neural Network. Analyzing the performance of each model based on the dataset.

The code for the ACL 2023 paper "Linear Classifier: An Often-Forgotten Baseline for Text Classification".

A comprehensive approach on recognizing emotion (sentiment) from a certain tweet. Supervised machine learning.

Aims at attributing the big-five personality traits to authors of essays by analyzing their works.

Visualising stock price predictions for several Machine Learning models using DASH, Python

Machine Learning, EDA, Binary Classification task weather dataset, ANN, SVM, LR

This app is intended to dynamically integrate machine learning techniques to explore multivariate data sets.

This project compares the accuracy of different machine learning models in the identification and classification of bearing faults from time-series vibration data.

Accelerated implementation of the SVM algorithm on an embedded SoC with changes to the algorithm structure to accommodate learning from large volumes of data in an incremental manner with approximations to the computations.

Machine learning coursera by Andrew Ng

This repository contains Python Implementation of certain programming assignments of Andrew Ng’s Machine Learning Course on Coursera, created by Stanford University.