S-Black's Stars
visenger/awesome-mlops
A curated list of references for MLOps
lmcinnes/umap
Uniform Manifold Approximation and Projection
jupyterlab/jupyterlab-desktop
JupyterLab desktop application, based on Electron.
awslabs/deequ
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
scikit-learn-contrib/hdbscan
A high performance implementation of HDBSCAN clustering.
tradytics/eiten
Statistical and Algorithmic Investing Strategies for Everyone
MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
arviz-devs/arviz
Exploratory analysis of Bayesian models with Python
stan-dev/example-models
Example models for Stan
shuyo/iir
Machine Learning / Natural Language Processing / Information Retrieval
shakedzy/dython
A set of data tools in Python
echen/dirichlet-process
Introduction to Nonparametric Bayes, Infinite Mixture Models, and the Dirichlet Process (+ McDonald's)
bnpy/bnpy
Bayesian nonparametric machine learning for Python
blei-lab/online-hdp
Online inference for the Hierarchical Dirichlet Process. Fits hierarchical Dirichlet process topic models to massive data. The algorithm determines the number of topics.
dsteinberg/libcluster
An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.
nicolaroberts/hdp
R pkg for Hierarchical Dirichlet Process
dm13450/dirichletprocess
Build dirichletprocess objects for data analysis
BGU-CS-VIL/DPMMSubClusters.jl
Distributed MCMC Inference in Dirichlet Process Mixture Models (High Performance Machine Learning Workshop 2019)
Shamir-Lab/Multi-Omics-Cancer-Benchmark
saeidamiri1/rbox
Hesamalian/HDP
Python code for HDP(Hierarchical Dirichlet Process) using Direct Assignment
mwestt/An-Introduction-to-Bayesian-Inference-in-PyStan
Code for blog post on Bayesian inference in PyStan
lee813/pydpmm
Direct Gibbs sampling for DPMM using python.
evelinag/clusternomics
Integrative clustering for heterogeneous biomedical datasets.
hammerlab/stanity
python convenience functions for working with Stan models (via pystan)
sarawade/mcclust.ext
This is an extension of the mcclust package. It provides post-processing tools for MCMC samples of partitions to summarize the posterior in Bayesian clustering models. Functions for point estimation are provided, giving a single representative clustering of the posterior. And, to characterize uncertainty in the point estimate, credible balls can be computed.
cran/NestedCategBayesImpute
:exclamation: This is a read-only mirror of the CRAN R package repository. NestedCategBayesImpute — Modeling, Imputing and Generating Synthetic Versions of Nested Categorical Data in the Presence of Impossible Combinations
eleafeit/data_fusion
Code for the examples in the Feit and Bradlow chapter on Fusion Modeling in the Handbook of Marketing Research.
svetamorag/BooksGenAI
yunjhongwu/dirichlet-process-demo
Visualizing clustering with Dirichlet processes