There are 12 repositories under support-vector-machines topic.

## Avik-Jain / 100-Days-Of-ML-Code

100 Days of ML Coding

## accord-net / framework

Machine learning, computer vision, statistics and general scientific computing for .NET

## anfederico / clairvoyant

Software designed to identify and monitor social/historical cues for short term stock movement

## kk7nc / Text_Classification

Text Classification Algorithms: A Survey

text-classificationnlp-machine-learningdocument-classificationtext-processingdimensionality-reductionrocchio-algorithmboosting-algorithmslogistic-regressionnaive-bayes-classifierk-nearest-neighbourssupport-vector-machinesdecision-treesrandom-forestconditional-random-fieldsdeep-learningdeep-neural-networkrecurrent-neural-networksconvolutional-neural-networksdeep-belief-networkhierarchical-attention-networks## nsoojin / coursera-ml-py

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

## jmartinezheras / 2018-MachineLearning-Lectures-ESA

Machine Learning Lectures at the European Space Agency (ESA) in 2018

## Madhu009 / Deep-math-machine-learning.ai

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

machine-learninglinear-regressiontensorflowgradient-descent-algorithmlogistic-regressionsupport-vector-machinesdeep-neural-networksword2vecnatural-language-processingreinforcement-learning-algorithmspolicy-iterationvalue-iterationmonte-carlo-methodstemporal-differencing-learningq-learningsarsageneral-adversarial-networkgansneural-networks## gionanide / Speech_Signal_Processing_and_Classification

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

speech-processingmfcclinear-prediction-coefficientsclassifierspeech-utterancefeature-extractionsupport-vector-machinesgaussian-mixture-modelslong-short-term-memoryprincipal-component-analysiskernel-pcalinear-discriminant-analysisisomaplocally-linear-embeddingspectral-embeddingspectral-clusteringnatural-language-processingnlpnltk## snrazavi / Machine_Learning_2018

Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz

## DoubangoTelecom / compv

Insanely fast Open Source Computer Vision library for ARM and x86 devices (Up to #50 times faster than OpenCV)

## GeorgeSeif / Python-Machine-Learning

Python Machine Learning Algorithms

## mithi / vehicle-tracking-2

A vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM).

## hiroyuki-kasai / ClassifierToolbox

A MATLAB toolbox for classifier: Version 1.0.7

## sharmapratik88 / AIML-Projects

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

supervised-machine-learningmachine-learningknearest-neighbor-algorithmrandom-forestmachinelearningprojectsunsupervised-machine-learninglogistic-regressionsupport-vector-machinesdecision-tree-classifiergradient-boosting-classifierstatisticsensemble-machine-learningoversamplingdata-sciencedata-visualizationdatascienceprojectrecommendation-systemcatboostnlpcomputer-vision## shawn-terryah / Twitter_Geolocation

Geolocating twitter users by the content of their tweets

## tiskw / random-fourier-features

Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model

## CihanBosnali / Machine-Learning-without-Libraries

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

## decile-team / jensen

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.)

## OSSpk / Handwritten-Digits-Classification-Using-KNN-Multiclass_Perceptron-SVM

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

comparative-studymachine-learning-algorithmssupervised-machine-learningk-nearest-neighbourssupport-vector-machinessupport-vector-classifiermulticlass-perceptronartificial-neural-networklearning-algorithms-comparisonhandwritten-digit-recognitionmnist-datasetmnist-classification-logisticdelta-ruleperceptron-learning-algorithmaccuracy-analysisefficiency-analysislogistic-regressionsigmoid-functionknnsvm## abhinavsagar / ICC-2019-WC-prediction

Predicting the winner of 2019 cricket world cup using random forest algorithm

## Mamcose / NSL-KDD-Network-Intrusion-Detection

Machine Learning Algorithms on NSL-KDD dataset

## zhaoyichanghong / machine_learing_algo_python

implement the machine learning algorithms by python for studying

machine-learningdeep-learningneural-networkkmeansgaussian-mixture-modelslinear-discriminant-analysissupport-vector-machinesprincipal-component-analysislinear-regressionlogistic-regressionadaboostgaussian-discriminant-analysisk-nearest-neighbordecision-treegbdtrbf-networkspectral-clusteringcollaborative-filteringtf-idfisolation-forest## bank-of-england / Shapley_regressions

Statistical inference on machine learning or general non-parametric models

## hiroyuki-kasai / SparseGDLibrary

MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3

admmalgorithmsbig-datacoordinate-descentelasticnetgradient-descentlassolasso-regressionlogistic-regressionmachine-learningmachine-learning-algorithmsmatrix-completionoptimizationoptimization-algorithmsproximal-algorithmsproximal-operatorssolversparse-linear-solversparse-regressionsupport-vector-machines## tirthajyoti / R-stats-machine-learning

Misc Statistics and Machine Learning codes in R

## krish240574 / ETFMachineLearning

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

## MrKhan0747 / Diabetes-Prediction

Machine learning approach to detect whether patien has the diabetes or not. Data cleaning, visualization, modeling and cross validation applied

## qandeelabbassi / python-svm-sgd

Python implementation of stochastic sub-gradient descent algorithm for SVM from scratch

## abdullahselek / spampy

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

## neerajd12 / object-detection-with-svm-and-opencv

detect objects using svm and opencv

## alicex2020 / Deep-Learning-Lie-Detection

Use machine learning models to detect lies based solely on acoustic speech information

## primaryobjects / fashion

The Fashion-MNIST dataset and machine learning models.