Clustering.jl by JuliaStats

A Julia package for data clustering

created at Nov. 24, 2012, 3:47 p.m.

Julia

21 +0

355 +0

118 +0

GitHub
bigartm by bigartm

Fast topic modeling platform

created at Sept. 15, 2014, 8:26 p.m.

C++

41 +0

662 +0

117 +0

GitHub
torch-autograd by twitter-archive

Autograd automatically differentiates native Torch code

created at Oct. 6, 2015, 2:51 p.m.

Lua

50 +0

560 +0

115 +0

GitHub
GLM.jl by JuliaStats

Generalized linear models in Julia

created at May 30, 2012, 3:30 a.m.

Julia

30 +0

595 +0

114 +0

GitHub
enlighten-apply by sassoftware

Example code and materials that illustrate applications of SAS machine learning techniques.

created at May 8, 2015, 3:20 p.m.

SAS

45 +0

126 +0

113 +0

GitHub
cortex by thinktopic

Machine learning in Clojure

created at Sept. 27, 2016, 5:03 p.m.

Clojure

108 +0

1,271 +0

111 +0

GitHub
AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics by Western-OC2-Lab

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

created at Sept. 9, 2022, 3:01 a.m.

Jupyter Notebook

70 +0

624 +1

111 +0

GitHub
XGBoost.jl by dmlc

XGBoost Julia Package

created at Aug. 14, 2014, 7:10 p.m.

Julia

26 +0

289 +0

110 +0

GitHub
bioruby by bioruby

bioruby

created at June 18, 2008, 12:45 p.m.

Ruby

36 +0

378 +0

109 +0

GitHub
DSP.jl by JuliaDSP

Filter design, periodograms, window functions, and other digital signal processing functionality

created at Nov. 27, 2013, 11:35 p.m.

Julia

30 +0

381 +0

109 -1

GitHub
Pyevolve by perone

Pyevolve

created at Aug. 10, 2011, 11:41 p.m.

Python

32 +0

315 +1

108 +1

GitHub
mlens by flennerhag

ML-Ensemble – high performance ensemble learning

created at Jan. 10, 2017, 8:53 p.m.

Python

28 +0

847 +0

108 +0

GitHub
detecto by alankbi

Build fully-functioning computer vision models with PyTorch

created at Dec. 11, 2019, 9:50 p.m.

Python

23 +0

613 +0

107 +0

GitHub
libonnx by xboot

A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.

created at Oct. 14, 2020, 1:20 a.m.

C

28 +1

583 +2

107 -1

GitHub
instill-core by instill-ai

🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications

created at Jan. 13, 2022, 1:27 p.m.

Makefile

30 +0

2,146 +23

107 +1

GitHub
go-geom by twpayne

Package geom implements efficient geometry types for geospatial applications.

created at March 6, 2014, 1:39 p.m.

Go

15 +0

856 +2

106 +0

GitHub
xcessiv by reiinakano

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

created at March 7, 2017, 6:18 p.m.

Python

55 +0

1,267 +0

105 +0

GitHub
kotlindl by Kotlin

High-level Deep Learning Framework written in Kotlin and inspired by Keras

created at March 25, 2020, 10:27 a.m.

Kotlin

43 +0

1,474 +5

103 +0

GitHub
Auto_ViML by AutoViML

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

created at June 10, 2019, 1:09 p.m.

Python

26 +0

524 +0

102 +0

GitHub
chefboost by serengil

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

created at March 6, 2019, 12:26 p.m.

Python

18 +0

460 +2

101 +0

GitHub