Search Results for "k-means clustering delphi"
Sort By:
Showing 89 open source projects for "k-means clustering delphi"
View related business solutions-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
1
Clustering.jl
A Julia package for data clustering
Methods for data clustering and evaluation of clustering quality. -
2
MatlabMachine
Machine learning algorithms
Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts. -
3
Machine Learning Octave
MatLab/Octave examples of popular machine learning algorithms
This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on... -
4
HDBSCAN
A high performance implementation of HDBSCAN clustering
HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates the result to find a clustering that gives the best stability over epsilon. This allows HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more robust to parameter selection. In practice this means that HDBSCAN returns a good clustering straight away with little or no parameter tuning -- and the primary parameter, minimum cluster size, is intuitive and easy to select. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
5
dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
6
HyperTools
A Python toolbox for gaining geometric insights
...Functions for plotting high-dimensional datasets in 2/3D. Static and animated plots. Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes, text or (mixed) lists. Applying topic models and other text vectorization methods to text data. HyperTools is designed to facilitate dimensionality reduction-based visual explorations of high-dimensional data. The basic pipeline is to feed in a high-dimensional dataset (or a series of high-dimensional datasets) and, in a single function call, reduce the dimensionality of the dataset(s) and create a plot. -
7
Homemade Machine Learning
Python examples of popular machine learning algorithms
...Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work. -
8
Machine learning algorithms
Minimal and clean examples of machine learning algorithms
Machine learning algorithms is an open-source repository that provides minimal and clean implementations of machine learning algorithms written primarily in Python. The project focuses on demonstrating how fundamental machine learning methods work internally by implementing them from scratch rather than relying on high-level libraries. This approach allows learners to study the mathematical and algorithmic details behind widely used models in a transparent and readable way. The repository... -
9
kube-state-metrics
Add-on agent to generate and expose cluster-level metrics
kube-state-metrics (KSM) is a simple service that listens to the Kubernetes API server and generates metrics about the state of the objects. (See examples in the Metrics section below.) It is not focused on the health of the individual Kubernetes components, but rather on the health of the various objects inside, such as deployments, nodes and pods. kube-state-metrics is about generating metrics from Kubernetes API objects without modification. This ensures that features provided by... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
10
SageMaker Spark
A Spark library for Amazon SageMaker
...These pipelines interleave native Spark ML stages and stages that interact with SageMaker training and model hosting. With SageMaker Spark, you can train on Amazon SageMaker from Spark DataFrames using Amazon-provided ML algorithms like K-Means clustering or XGBoost, and make predictions on DataFrames against SageMaker endpoints hosting your trained models, and, if you have your own ML algorithms built into SageMaker compatible Docker containers, you can use SageMaker Spark to train and infer on DataFrames with your own algorithms -- all at Spark scale. SageMaker Spark depends on hadoop-aws-2.8.1. ... -
11
Promxy
An aggregating proxy to enable HA prometheus
...Promxy delivers this unified access endpoint without requiring any sidecars, custom-builds, or other changes to your prometheus infrastructure. Prometheus itself provides no real HA/clustering support. As such the best-practice is to run multiple (e.g N) hosts with the same config. Similarly prometheus has no real built-in query federation, which means that you end up with N sources in grafana which is (1) confusing to grafana users and (2) has no support for aggregation across the sources. Promxy enables an HA prometheus setup by "merging" the data from the duplicate hosts (so if there is a gap in one, promxy will fill with the other). ... -
12
Dynamic Arrays and Hashes (Delphi, C++)
Very fast classes for working with Dynamic Arrays in Delphi and C++
(New version 1.04 is released) Dynamic Arrays is a set of useful very fast classes for data manipulating in memory. Flexible memory control, functionality that standard containers do not have, fast operations (assembler implementation for x86 and x64 platforms). Available for Delphi all latest versions and for C++. Powerful Hash and Double Hash classes to work with pairs of values (key and value) and with values that have two keys (key1, key2, value). Give it a try and let me know how... -
13
OptiMIClass
Automatic n-dimensional data clustering tool powered by five advanced
This software is an automatic n-dimensional quantitative data clustering tool based on five optimization heuristics (GA, PSO, ACO, SA, and TS). It enables performance comparisons across heuristics and parameter testing within each method, analyzing solution quality, runtime, and convergence; it also includes a repository of benchmark test tables and an intuitive interface for research and operational use. It was developed by M.Sc. Jeffry Chavarría-Molina and M.Sc. Juan José Fallas-Monge... -
14
Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
15
dzLargeTextViewer
Tool for displaying large (>2 GB) text files
This is a very simple tool for displaying large text files where large means they don't fit into the 2 GB memory which a 32 bit Windows process can use. I successfully tested it displaying a 48 GB XML dump of the English language Wikipedia which contained 789.577.286 lines of text. -
16
Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3... -
17
maXbox
maXbox: Precompiled Object Based Scripting Tool
maXbox: Precompiled Object Based Scripting Tool maXbox is a free scripter tool with an inbuilt object pascal delphi engine in one exe! It is designed for teaching, develop, test and analyzing apps and algorithms and runs under Win, Mac and Linux (CLX) to set code in a box without installation and no administration. The tool for 32 and 64-bit is based on an educational program with examples and exercises (from biorhythm, REST services , form building to how math works). Pure Code for Object... -
18
m23
Your linux deployment tool!
m23 is a free software distribution system (license: GPL), that installs (via network, starting with partitioning and formatting) and administrates (updates, adds / removes software, adds / removes scripts) clients with Debian, (X/K)Ubuntu and LinuxMint. It is used for deployment of Linux clients in schools, institutions and enterprises. The m23 server is controlled via a web interface. A new m23 client can be installed easily in only three steps. Group functions and mass installation... -
19
MooseFS
Fault tolerant, POSIX-compliant, Net Distributed Storage / File System
MooseFS (MFS) is a fault tolerant, highly performing, scaling-out, network distributed file system. It spreads data over several physical servers which are visible to the user as one resource. For standard file operations MooseFS mounted with FUSE acts as other Unix-alike file systems: * A hierarchical structure (directory tree) * Stores POSIX file attributes (permissions, last access and modification times) Supports special files (block and character devices, pipes and sockets) *... -
20
PDP-OmniSim
PDP-OmniSim simulating parallel and distributed processing systems
PDP-OmniSim 🧬 Scientific Overview PDP-OmniSim is an advanced computational framework for simulating parallel and distributed processing systems, with cutting-edge applications in computational neuroscience, distributed computing, and complex systems modeling. The framework provides researchers with robust tools for large-scale simulations of networked systems and their emergent behaviors. 🎯 Key Scientific Contributions 🔬 Interdisciplinary Research Domains Computational... -
21
MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
-
22
Texthero
Text preprocessing, representation and visualization from zero to hero
Texthero is a python package to work with text data efficiently. It empowers NLP developers with a tool to quickly understand any text-based dataset and it provides a solid pipeline to clean and represent text data, from zero to hero. -
23
sx-emcalc
Multifunctional electronics calculator
-
24
PyArmadillo
linear algebra library for Python
PyArmadillo - streamlined linear algebra library for Python, with emphasis on ease of use. Alternative to NumPy / SciPy. * Main page: https://pyarma.sourceforge.io * Documentation: https://pyarma.sourceforge.io/docs.html * Bug reports: https://pyarma.sourceforge.io/faq.html * Git repo: https://gitlab.com/jason-rumengan/pyarma -
25
DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups.
