54 Open source projects that are alternatives of or similar to Study-of-David-Mackay-s-book-

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

Implementing Genetic Algorithm on K-Means and compare with K-Means++

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.

Super fast simple k-means implementation for unidimiensional and multidimensional data.

Parallel & lightning fast implementation of available classic and contemporary variants of the KMeans clustering algorithm

Map SDK를 활용한 POI Clustering Interaction Dev.

Resolver Sudoku de genina.com

www.kelp-ml.org

Map SDK를 활용한 POI Clustering Interaction Dev

An unsupervised machine learning algorithm for the segmentation of spatial data sets.

No description or website provided.

k-means clustering in Ruby

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Different clustering approaches applied on different problemsets

C4E, a JVM friendly library written in Scala for both local and distributed (Spark) Clustering.

A fun study of some heuristics for the Travelling Salesman Problem.

interactive clustering platform

Clone identification from single-cell data

A high performance implementation of HDBSCAN clustering.

spatially-constrained clustering in R

Fast OPTICS clustering in Cython + gradient cluster extraction

Implements "Clustering a Million Faces by Identity"

Genie++ Fast and Robust Hierarchical Clustering with Noise Point Detection - for Python and R

Implementation of ST-DBSCAN algorithm based on Birant 2007

Elixir implementation of CLOPE: A Fast and Effective Clustering Algorithm for Transactional Data

An intuitive implementation of spectral clustering on matlab

Cluster analysis library for Golang

ADENINE: A Data ExploratioN PipelINE

Built on data from Pluralsight's course API fetched results. Works with model trained with K-means unsupervised clustering algorithm.

Python Clustering Algorithms

Single-cell exploratory data analysis for RNA-Seq

k-means clustering algorithm with k-means++ initialization.

A clustering tutorial with scikit-learn for beginners.

Implementation of the Neural Clustering Process algorithm in Pytorch

Code for Tensorflow Machine Learning Cookbook

Python code for common Machine Learning Algorithms

A data-driven tool to identify the best candidates for a marketing campaign and optimize it.

Implemented ML algorithms in hyperbolic geometry (MDS, K-Means, Support vector machines, etc.)

Machine Learning Course @ Santa Clara University

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

A C++ implementation of simple k-means clustering algorithm.

🍡 文本聚类 k-means算法及实战

🎨 Apply color quantization to images using k-means clustering.

Unsupervised Machine Learning: Nonnegative Tensor Factorization + k-means clustering

Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'

A C++ library of Markov Chain Monte Carlo (MCMC) methods

Application of the L2HMC algorithm to simulations in lattice QCD.

Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.

CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations

A Latent Dirichlet Allocation implementation in Python.

🐙: Maximum likelihood model estimation using scipy.optimize

A High Performance Unified Framework for Geostatistics on Manycore Systems.

Slides and notebooks for my tutorial at PyData London 2018