support-vector-machines

There are 14 repositories under support-vector-machines topic.

Avik-Jain / 100-Days-Of-ML-Code
100 Days of ML Coding
machine-learning machine-learning-algorithms infographics tutorial siraj-raval-challenge siraj-raval implementation 100-days-of-code-log 100daysofcode python logistic-regression naive-bayes-classifier linear-regression svm linear-algebra scikit-learn support-vector-machines deep-learning
43290
liuruoze / EasyPR
(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
computer-vision machine-learning artificial-intelligence plate-recognition unconstrained-situation datasets artificial-neural-networks support-vector-machines supervised-learning chinese-characters opencv opencv3
Language:C++ 6318
accord-net / framework
Machine learning, computer vision, statistics and general scientific computing for .NET
machine-learning framework c-sharp nuget visual-studio statistics unity3d neural-network support-vector-machines computer-vision image-processing ffmpeg
Language:C# 4441
anfederico / clairvoyant
Software designed to identify and monitor social/historical cues for short term stock movement
backtesting-trading-strategies machine-learning portfolio-simulation stock-market support-vector-machines
Language:Python 2400
kk7nc / Text_Classification
Text Classification Algorithms: A Survey
text-classification nlp-machine-learning document-classification text-processing dimensionality-reduction rocchio-algorithm boosting-algorithms logistic-regression naive-bayes-classifier k-nearest-neighbours support-vector-machines decision-trees random-forest conditional-random-fields deep-learning deep-neural-network recurrent-neural-networks convolutional-neural-networks deep-belief-network hierarchical-attention-networks
Language:Python 1777
nsoojin / coursera-ml-py
Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera
andrew-ng-course andrew-ng-ml-course coursera-machine-learning andrew-ng-machine-learning numpy-exercises machine-learning-ex1 neural-network support-vector-machines principal-component-analysis logistic-regression anomaly-detection python-ml
Language:Python 1357
Machine-Learning-Guide
mikeroyal / Machine-Learning-Guide
Machine learning Guide. Learn all about Machine Learning Tools, Libraries, Frameworks, Large Language Models (LLMs), and Training Models.
python deep-learning machine-learning-library machinelearning machine-learning-models pytorch machinelearning-python scikit-learn scikitlearn-machine-learning support-vector-machines gpt-3 aws-sagemaker artificial-neural-networks jax image-classification gpt-4 generative-ai image-processing gpt4all llms
Language:Python 432
jmartinezheras / 2018-MachineLearning-Lectures-ESA
Machine Learning Lectures at the European Space Agency (ESA) in 2018
machinelearning machine-learning linear-regression support-vector-machines decision-trees random-forest neural-network deep-learning clustering pca anomaly-detection text-mining tf-idf topic-modeling lectures lecture-slides lecture-material lecture-videos
Language:Jupyter Notebook 344
fukuball / fuku-ml
Simple machine learning library / 簡單易用的機器學習套件
machine-learning svm support-vector-machines classification regression linear-regression logistic-regression perceptron decision-trees neural-network
Language:Python 280
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].
classifier feature-extraction gaussian-mixture-models isomap kernel-pca linear-discriminant-analysis linear-prediction-coefficients locally-linear-embedding long-short-term-memory mfcc natural-language-processing nlp nltk principal-component-analysis spectral-clustering spectral-embedding speech-processing speech-utterance support-vector-machines
Language:Python 230
snrazavi / Machine_Learning_2018
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
machine-learning regression classification logistic-regression neural-networks support-vector-machines clustering dimensionality-reduction pca recommender-system anomaly-detection python linear-regression supervised-learning unsupervised-machine-learning gradient-descent backpropagation
Language:Jupyter Notebook 200
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.
deep-neural-networks gans general-adversarial-network gradient-descent-algorithm linear-regression logistic-regression machine-learning monte-carlo-methods natural-language-processing neural-networks policy-iteration q-learning reinforcement-learning-algorithms sarsa support-vector-machines temporal-differencing-learning tensorflow value-iteration word2vec
Language:Jupyter Notebook 198
DoubangoTelecom / compv
Insanely fast Open Source Computer Vision library for ARM and x86 devices (Up to #50 times faster than OpenCV)
computer-vision artificial-intelligence artificial-neural-networks machine-learning ocr-recognition text-recognition neural-network support-vector-machines boosting adaboost assembler arm x86 gpgpu-computing pattern-recognition
Language:C++ 180
sharmapratik88 / AIML-Projects
Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
supervised-machine-learning machine-learning knearest-neighbor-algorithm random-forest machinelearningprojects unsupervised-machine-learning logistic-regression support-vector-machines decision-tree-classifier gradient-boosting-classifier statistics ensemble-machine-learning oversampling data-science data-visualization datascienceproject recommendation-system catboost nlp computer-vision
Language:Jupyter Notebook 125
GeorgeSeif / Python-Machine-Learning
Python Machine Learning Algorithms
algorithm classification machine-learning neural-network python python-machine-learning regression scikit-learn support-vector-machines
Language:Python 92
mithi / vehicle-tracking-2
A vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM).
hog-features udacity vehicle-tracking support-vector-machines self-driving-car
Language:Jupyter Notebook 83
hiroyuki-kasai / ClassifierToolbox
A MATLAB toolbox for classifier: Version 1.0.7
face-recognition classification classification-algorithims covariance-matrix sparse-coding linear-regression linear-discriminant-analysis principal-component-analysis symmetric-positive-definite spd subspace manifold matlab-toolbox dictionary-learning manifold-optimization support-vector-machines src eigenfaces pca
Language:MATLAB 81
tiskw / random-fourier-features
Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
support-vector-machines python gaussian-processes principal-component-analysis pytorch machine-learning
Language:Python 79
shawn-terryah / Twitter_Geolocation
Geolocating twitter users by the content of their tweets
tweepy twitter-geolocation natural-language-processing stacked-ensembles geolocation twitter-streaming-api support-vector-machines random-forest maps amazon-web-services
Language:Python 78
Mamcose / NSL-KDD-Network-Intrusion-Detection
Machine Learning Algorithms on NSL-KDD dataset
nsl-kdd-dataset random-forest k-nearest-neighbors support-vector-machines ensemble-learning machine-learning validation
Language:Jupyter Notebook 77
MrKhan0747 / Diabetes-Prediction
Machine learning approach to detect whether patien has the diabetes or not. Data cleaning, visualization, modeling and cross validation applied
diabetes diabetes-prediction diabetes-detection detection machine-learning logistic-regression support-vector-machines random-forest-classifier knn-classification naive-bayes-classifier accuracy machine-learning-algorithms health-data
Language:Jupyter Notebook 71
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-study machine-learning-algorithms supervised-machine-learning k-nearest-neighbours support-vector-machines support-vector-classifier multiclass-perceptron artificial-neural-network learning-algorithms-comparison handwritten-digit-recognition mnist-dataset mnist-classification-logistic delta-rule perceptron-learning-algorithm accuracy-analysis efficiency-analysis logistic-regression sigmoid-function knn svm
Language:Python 59
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
k-means-clustering machine-learning k-nearest-neighbors support-vector-machines neural-networks machine-learning-algorithms
Language:Jupyter Notebook 56
hiroyuki-kasai / SparseGDLibrary
MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3
optimization optimization-algorithms machine-learning-algorithms machine-learning big-data gradient-descent sparse-linear-solver sparse-regression lasso-regression lasso elasticnet solver algorithms admm proximal-algorithms proximal-operators logistic-regression matrix-completion coordinate-descent support-vector-machines
Language:MATLAB 51
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.)
machine-learning machine-learning-algorithms convex-optimization lbfgs-algorithm sgd logistic-regression support-vector-machines gradient-descent optimization-algorithms jensen tron lbfgs regularization
Language:C++ 49
zhaoyichanghong / machine_learing_algo_python
implement the machine learning algorithms by python for studying
machine-learning deep-learning neural-network kmeans gaussian-mixture-models linear-discriminant-analysis support-vector-machines principal-component-analysis linear-regression logistic-regression adaboost gaussian-discriminant-analysis k-nearest-neighbor decision-tree gbdt rbf-network spectral-clustering collaborative-filtering tf-idf isolation-forest
Language:Python 44
DSPKM / DSPKM
This is the page for the book Digital Signal Processing with Kernel Methods.
digital-signal-processing kernel-methods machine-learning support-vector-machines svm
Language:MATLAB 42
alicex2020 / Deep-Learning-Lie-Detection
Use machine learning models to detect lies based solely on acoustic speech information
machine-learning deep-learning mfcc mfcc-analysis lie-detector acoustic-features pitch-tracking support-vector-machines ensemble-learning ensemble-model ensemble-classifier ensemble-machine-learning
Language:Jupyter Notebook 40
bank-of-england / Shapley_regressions
Statistical inference on machine learning or general non-parametric models
machine-learning artificial-intelligence artificial-neural-networks statistical-inference statistical-tests non-parametric-inference time-series shapley-decomposition data-analysis simulation-modeling support-vector-machines random-forest
Language:Python 39
tirthajyoti / R-stats-machine-learning
Misc Statistics and Machine Learning codes in R
r machine-learning statistics regression principal-component-analysis classification support-vector-machines neural-network clustering k-means hypothesis-testing nearest-neighbors random-forest decision-trees
Language:R 39
krish240574 / ETFMachineLearning
Implementation of a paper in q/KDB+ and python - "Forecasting ETFs with Machine Learning Algorithms" - Jim Kyung-Soo Liew and Boris Mayster
quantitative-trading neural-networks deep-learning random-forest support-vector-machines kdb kx python
Language:Jupyter Notebook 36
MaviccPRP / svm
Tutorial: Support Vector Machine from scratch using Python3
support-vector-machines svm machine-learning machine-learning-tutorials
Language:Jupyter Notebook 36
qandeelabbassi / python-svm-sgd
Python implementation of stochastic sub-gradient descent algorithm for SVM from scratch
python machine-learning support-vector-machines stochastic-gradient-descent numpy pandas
Language:Python 35
carmelgafa / ml-from-scratch
ML algorithms from scratch
fuzzy-logic id3 k-means machine-learning-algorithms regression support-vector-machines
Language:Python 33
nishi1612 / Email-Spam-Classification-using-SVM
The uploaded codes help to classify emails into spam and non spam classes by using Support Vector Machine classifier.
support-vector-machines email-spam-filter machine-learning-algorithms lemmatization stopwords-removal binary-classifier
Language:Python 29
jrothschild33 / Fudan-DataMining
2020 Spring Fudan University Data Mining Course HW by prof. Zhu Xuening. 复旦大学大数据学院2020年春季课程-数据挖掘（DATA620007）包含数据挖掘算法模型：Linear Regression Model、Logistic Regression Model、Linear Discriminant Analysis、K-Nearest Neighbour、Naive Bayes Classifier、Decision Tree Model、AdaBoost、Gradient Boosting Decision Tree(GBDT)、XGBoost、Random Forest Model、Support Vector Machine、Principal Component Analysis(PCA)
linear-regression logistic-regression knn-classification naive-bayes-classifier data-mining decision-trees adaboost gbdt xgboost random-forest support-vector-machines pca-analysis
Language:Jupyter Notebook 28

support-vector-machines

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

liuruoze / EasyPR

accord-net / framework

anfederico / clairvoyant

kk7nc / Text_Classification

nsoojin / coursera-ml-py

mikeroyal / Machine-Learning-Guide

jmartinezheras / 2018-MachineLearning-Lectures-ESA

fukuball / fuku-ml

gionanide / Speech_Signal_Processing_and_Classification

snrazavi / Machine_Learning_2018

Madhu009 / Deep-math-machine-learning.ai

DoubangoTelecom / compv

sharmapratik88 / AIML-Projects

GeorgeSeif / Python-Machine-Learning

mithi / vehicle-tracking-2

hiroyuki-kasai / ClassifierToolbox

tiskw / random-fourier-features

shawn-terryah / Twitter_Geolocation

Mamcose / NSL-KDD-Network-Intrusion-Detection

MrKhan0747 / Diabetes-Prediction

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

CihanBosnali / Machine-Learning-without-Libraries

hiroyuki-kasai / SparseGDLibrary

decile-team / jensen

zhaoyichanghong / machine_learing_algo_python

DSPKM / DSPKM

alicex2020 / Deep-Learning-Lie-Detection

bank-of-england / Shapley_regressions

tirthajyoti / R-stats-machine-learning

krish240574 / ETFMachineLearning

MaviccPRP / svm

qandeelabbassi / python-svm-sgd

carmelgafa / ml-from-scratch

nishi1612 / Email-Spam-Classification-using-SVM

jrothschild33 / Fudan-DataMining