support-vector-machine

nivu/ai_all_resources

A curated list of Best Artificial Intelligence Resources

mbeyeler/opencv-machine-learning

M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.

x4nth055/emotion-recognition-using-speech

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

mondejar/ecg-classification

Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database

Skylark0924/Machine-Learning-is-ALL-You-Need

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

srafay/Machine_Learning_A-Z

Learning to create Machine Learning Algorithms

AFAgarap/cnn-svm

An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification

ksopyla/svm_mnist_digit_classification

MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.

je-suis-tm/machine-learning

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

HongZhaoHua/jstarcraft-ai

目标是提供一个完整的Java机器学习(Machine Learning/ML)框架,作为人工智能在学术界与工业界的桥梁. 让相关领域的研发人员能够在各种软硬件环境/数据结构/算法/模型之间无缝切换. 涵盖了从数据处理到模型的训练与评估各个环节,支持硬件加速和并行计算,是最快最全的Java机器学习库.

YGZWQZD/LAMDA-SSL

30 Semi-Supervised Learning Algorithms

AFAgarap/malware-classification

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

AFAgarap/gru-svm

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

Anmol-Singh-Jaggi/Sign-Language-Recognition

:v: :ok_hand: :fist: :camera: Sign Language Recognition using Python

ayrna/orca

Ordinal Regression and Classification Algorithms

ahmetozlu/vehicle_counting_hog_svm

Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.

dgriffiths3/ml_segmentation

Machine learning semantic segmentation - Random Forest, SVM, GBC

lauerfab/MLweb

Machine learning and scientific computing (linear algebra, statistics, optimization) javascript libraries, with an online lab.

mljs/libsvm

LIBSVM for the browser and nodejs :fire:

snatch59/cnn-svm-classifier

Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine

whimian/SVM-Image-Classification

Image Classification with `sklearn.svm`

AFAgarap/wisconsin-breast-cancer

[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

HaotianMXu/Multiclass_LinearSVM_with_SGD

A demonstration of how to use PyTorch to implement Support Vector Machine with L2 regularizition and multiclass hinge loss

PacktWorkshops/The-Deep-Learning-with-Keras-Workshop

An Interactive Approach to Understanding Deep Learning with Keras

ymattu/MlBayesOpt

R package to tune parameters for machine learning(Support Vector Machine, Random Forest, and Xgboost), using bayesian optimization with gaussian process

nsoojin/coursera-ml-py-sj

mahesh147/Support-Vector-Machine

A simple implementation of support vector machine classifier in python.

mljs/svm

Support Vector Machine in Javascript

sksoumik/Forecasting-Weather-Using-Machine-Learning

Forecasting weather Using Multinomial Logistic Regression, Decision Tree, Naïve Bayes Multinomial, and Support Vector Machine

cloudera/CML_AMP_Anomaly_Detection

Apply modern, deep learning techniques for anomaly detection to identify network intrusions.

PacktWorkshops/The-Machine-Learning-Workshop

An interactive approach to understanding Machine Learning using scikit-learn

LorranSutter/PredictStock-SVM

ML model for stock trend prediction using Python

pdhimal1/AI-Project

Stock predictor using Machine Learning

BeeGass/Self-Taught-Machine-Learning

I have had trouble in the past finding a place where I could learn about statistical learning algorithms, resources as to how to learn them and the code associated with it. This is my attempt at remedying that issue.

mo26-web/Induction-Motor-Faults-Detection-with-Stacking-Ensemble-Method-and-Deep-Learning

This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.