Pca MagicPCA that iteratively replaces missing data
Parameters📊 Computation and processing of models' parameters
AresA Python library for adversarial machine learning focusing on benchmarking adversarial robustness.
Ml CourseStarter code of Prof. Andrew Ng's machine learning MOOC in R statistical language
Miscellaneous R CodeCode that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.
Machine Learning In RWorkshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
Msmbuilder🏗 Statistical models for biomolecular dynamics 🏗
Isl PythonSolutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
VizukaExplore high-dimensional datasets and how your algo handles specific regions.
RistrettoRandomized Dimension Reduction Library
Half SizeCode for "Effective Dimensionality Reduction for Word Embeddings".
Ml codeA repository for recording the machine learning code
Patternrecognition matlabFeature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).
PlnmodelsA collection of Poisson lognormal models for multivariate count data analysis
AilearningAiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
PalmnetSource code for the 2019 IEEE TIFS paper "PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition"
NannyA tidyverse suite for (pre-) machine-learning: cluster, PCA, permute, impute, rotate, redundancy, triangular, smart-subset, abundant and variable features.
H2o 3H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Prince👑 Python factor analysis library (PCA, CA, MCA, MFA, FAMD)
CilantroA lean C++ library for working with point cloud data
fitFusion ICA Toolbox (MATLAB)
motionLibquaternion, euler angle, interpolation, cubic bezier, cubic spline, PCA, etc.
HRTF-IndividualizationHead-related Transfer Function Customization Process through Slider using PCA and SH in Matlab
NMFADMMA sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).
NIDS-Intrusion-DetectionSimple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN
FSCNMFAn implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".
mnist-challengeMy solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
pcaPrincipal component analysis (PCA) in Ruby
models-by-exampleBy-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
Universal Head 3DMMThis is a Project Page of 'Towards a complete 3D morphable model of the human head'
VisualMLInteractive Visual Machine Learning Demos.
SpatPCAR Package: Regularized Principal Component Analysis for Spatial Data
PerfSpectsystem performance characterization tool based on linux perf
data-science-learning📊 All of courses, assignments, exercises, mini-projects and books that I've done so far in the process of learning by myself Machine Learning and Data Science.
AnnA Anki neuronal AppendixUsing machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity
SNPRelateR package: parallel computing toolset for relatedness and principal component analysis of SNP data (Development Version)
geeSharp.jsPan-sharpening in the Earth Engine code editor
mosesStreaming, Memory-Limited, r-truncated SVD Revisited!