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lrr

Low-Rank Representation Python implementation

machine-learning

my machine-learning tutorial

mlalgorithms

Minimal and clean examples of machine learning algorithms

models

Models and examples built with TensorFlow

my_gcforest

neural_network_cracking

Code for cracking passwords with neural networks

nips2014-survey

Survey of hyperparameter optimization use in NIPS2014

pylearningcurvepredictor

predicting learning curves in python

robo

RoBO: a Robust Bayesian Optimization framework

skdata

Data sets for machine learning in Python

smac3

Sequential Model-based Algorithm Configuration

sparse-subspace-clustering

spearmint

Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012

subkit

Subspace Clustering Library

tf-tutorials

A collection of deep learning tutorials using Tensorflow and Python

tf_rnnlm

Language Modeling with RNN using TensorFlow

the-gan-zoo

A list of all named GANs!

using-machine-learning-to-detect-malicious-urls

Machine Learning and Security | Using machine learning to detect malicious URLs

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

ytk-learn

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax, SVM).