TribuoTribuo - A Java machine learning library
Stars: ✭ 882 (+76.05%)
MlboxMLBox is a powerful Automated Machine Learning python library.
Stars: ✭ 1,199 (+139.32%)
MetriculousMeasure and visualize machine learning model performance without the usual boilerplate.
Stars: ✭ 71 (-85.83%)
Openml RR package to interface with OpenML
Stars: ✭ 81 (-83.83%)
Bayesian Neural NetworksPytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Stars: ✭ 900 (+79.64%)
ThundersvmThunderSVM: A Fast SVM Library on GPUs and CPUs
Stars: ✭ 1,282 (+155.89%)
Malware ClassificationTowards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification
Stars: ✭ 88 (-82.44%)
drupal9ciOne-line installers for implementing Continuous Integration in Drupal 9
Stars: ✭ 137 (-72.65%)
EmbeddedMLEmbeddedML was created to be an alternative to the limited options available for Artificial Neural Networks in C. It is designed to be efficient without sacrificing ease of use. It is meant to support students as well as industry experts as it is built to be expandable and straightforward to manipulate.
Stars: ✭ 24 (-95.21%)
MlA high-level machine learning and deep learning library for the PHP language.
Stars: ✭ 1,270 (+153.49%)
Tiny mlnumpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法
Stars: ✭ 129 (-74.25%)
EjmlA fast and easy to use linear algebra library written in Java for dense, sparse, real, and complex matrices.
Stars: ✭ 378 (-24.55%)
SnapeSnape is a convenient artificial dataset generator that wraps sklearn's make_classification and make_regression and then adds in 'realism' features such as complex formating, varying scales, categorical variables, and missing values.
Stars: ✭ 155 (-69.06%)
Data Science ToolkitCollection of stats, modeling, and data science tools in Python and R.
Stars: ✭ 169 (-66.27%)
Machine Learning With PythonPractice and tutorial-style notebooks covering wide variety of machine learning techniques
Stars: ✭ 2,197 (+338.52%)
Uci Ml ApiSimple API for UCI Machine Learning Dataset Repository (search, download, analyze)
Stars: ✭ 190 (-62.08%)
Sparse Evolutionary Artificial Neural NetworksAlways sparse. Never dense. But never say never. A repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).
Stars: ✭ 182 (-63.67%)
DeepfashionApparel detection using deep learning
Stars: ✭ 223 (-55.49%)
FmatvecA fast vector/matrix library
Stars: ✭ 5 (-99%)
VectoriousLinear algebra in TypeScript.
Stars: ✭ 616 (+22.95%)
Fuku MlSimple machine learning library / 簡單易用的機器學習套件
Stars: ✭ 280 (-44.11%)
LibxsmmLibrary for specialized dense and sparse matrix operations, and deep learning primitives.
Stars: ✭ 518 (+3.39%)
Math PhpPowerful modern math library for PHP: Features descriptive statistics and regressions; Continuous and discrete probability distributions; Linear algebra with matrices and vectors, Numerical analysis; special mathematical functions; Algebra
Stars: ✭ 2,009 (+301%)
Eigen Git MirrorTHIS MIRROR IS DEPRECATED -- New url: https://gitlab.com/libeigen/eigen
Stars: ✭ 1,659 (+231.14%)
SmileStatistical Machine Intelligence & Learning Engine
Stars: ✭ 5,412 (+980.24%)
HaxeCIAn example of using CI for Haxe projects.
Stars: ✭ 45 (-91.02%)
scikit-ciSimpler and centralized CI configuration for Python extensions.
Stars: ✭ 15 (-97.01%)
combining3DmorphablemodelsProject Page of Combining 3D Morphable Models: A Large scale Face-and-Head Model - [CVPR 2019]
Stars: ✭ 80 (-84.03%)
mir-glas[Experimental] LLVM-accelerated Generic Linear Algebra Subprograms
Stars: ✭ 99 (-80.24%)
fmlFused Matrix Library
Stars: ✭ 24 (-95.21%)
docker-ci-deployPython script to help push Docker images to a registry using CI services
Stars: ✭ 20 (-96.01%)
ugtmugtm: a Python package for Generative Topographic Mapping
Stars: ✭ 34 (-93.21%)
noise-phpA starter-kit for your PHP project.
Stars: ✭ 52 (-89.62%)
Machine-Learning-SpecializationProject work and Assignments for Machine learning specialization course on Coursera by University of washington
Stars: ✭ 27 (-94.61%)
cpp14-project-templateA simple, cross-platform, and continuously integrated C++14 project template
Stars: ✭ 64 (-87.23%)
InstantDLInstantDL: An easy and convenient deep learning pipeline for image segmentation and classification
Stars: ✭ 33 (-93.41%)
Clean Marvel KotlinThis repository contains a detailed sample app that implements Clean architecture and MVP in Kotlin using RxJava2, Retrofit
Stars: ✭ 27 (-94.61%)
PyGLMFast OpenGL Mathematics (GLM) for Python
Stars: ✭ 167 (-66.67%)
LocalSupportA directory of local support services and volunteer opportunities
Stars: ✭ 60 (-88.02%)
stgPython/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)
Stars: ✭ 47 (-90.62%)
RAll Algorithms implemented in R
Stars: ✭ 294 (-41.32%)
sabotagea radical and experimental distribution based on musl libc and busybox
Stars: ✭ 502 (+0.2%)
data-science-notesOpen-source project hosted at https://makeuseofdata.com to crowdsource a robust collection of notes related to data science (math, visualization, modeling, etc)
Stars: ✭ 52 (-89.62%)
pywedgeMakes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking
Stars: ✭ 49 (-90.22%)
Predictive-Maintenance-of-Aircraft-EngineIn this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.
Stars: ✭ 48 (-90.42%)
AlphapyAutomated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost
Stars: ✭ 564 (+12.57%)
BlasjsPure Javascript manually written 👌 implementation of BLAS, Many numerical software applications use BLAS computations, including Armadillo, LAPACK, LINPACK, GNU Octave, Mathematica, MATLAB, NumPy, R, and Julia.
Stars: ✭ 241 (-51.9%)
ProbQAProbabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.
Stars: ✭ 43 (-91.42%)
Synthetic-data-genVarious methods for generating synthetic data for data science and ML
Stars: ✭ 57 (-88.62%)
PycaretAn open-source, low-code machine learning library in Python
Stars: ✭ 4,594 (+816.97%)
Go DeepArtificial Neural Network
Stars: ✭ 303 (-39.52%)