Search Results for "k-stor"
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Showing 96 open source projects for "k-stor"
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1
GoAWK
A POSIX-compliant AWK interpreter written in Go, with CSV support
GoAWK now uses a bytecode compiler and includes native support for CSV files. AWK is a fascinating text processing language, and The AWK Programming Language is a wonderfully concise book describing it. The A, W, and K in AWK stand for the surnames of the three original creators: Alfred Aho, Peter Weinberger, and Brian Kernighan. Kernighan is also an author of The C Programming Language (“K&R”), and the two books have that same each-page-packs-a-punch feel. AWK was released in 1977, which makes it over 40 years old! Not bad for a domain-specific language that’s still used for one-liners on Unix command lines everywhere. ... -
2
DocArray
The data structure for multimodal data
...Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases. -
3
Kubie
A more powerful alternative to kubectx and kubens
kubie is an alternative to kubectx, kubens, and the k on prompt modification script. It offers context switching, namespace switching, and prompt modification in a way that makes each shell independent from others. It also has support for split configuration files, meaning it can load Kubernetes contexts from multiple files. You can configure the paths where Kubie will look for contexts, see the settings section. -
4
kubeinvaders
Gamified Chaos Engineering Tool for Kubernetes
This project is part of the landscape of Cloud Native Computing Foundation in the Observability and Analysis - Chaos Engineering section. Backed by the teams at platform engineering.it and devopstribe.it, which provides enterprise-grade features and certified resilience services for your Kubernetes infrastructure. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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5
better-escape.nvim
Map keys without delay when typing
A lot of people have mappings like jk or jj to escape insert mode. The problem with these mappings is that whenever you type a j, neovim wait about 100-500ms (depending on your timeoutlen) to see if you type a j or a k because these are mapped. Only after that time, the j will be inserted. Then you always get a delay when typing a j. -
6
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... -
7
DashMap
Blazing fast concurrent HashMap for Rust
...DashMap tries to implement an easy-to-use API similar to std::collections::HashMap with some slight changes to handle concurrency. DashMap tries to be very simple to use and to be a direct replacement for RwLock<HashMap<K, V>>. To accomplish these goals, all methods take &self instead of modifying methods taking &mut self. This allows you to put a DashMap in an Arc<T> and share it between threads while still being able to modify it. DashMap puts great effort into performance and aims to be as fast as possible. If you have any suggestions or tips do not hesitate to open an issue or a PR. -
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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... -
9
Hotkeys JS
A robust Javascript library for capturing keyboard input
hotkeys-js is a tiny, framework-agnostic library for binding keyboard shortcuts in the browser, from simple key presses to complex combos and sequences. It provides a declarative API to register handlers like ctrl+k, shift+alt+p, or g g, and it normalizes key behavior across major browsers. The library includes scoping, so the same shortcut can trigger different actions depending on page context, and it offers filters to ignore inputs when the user is typing in form fields. You can enable or disable groups of shortcuts dynamically, making it well suited for SPAs and dashboard apps. ... -
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10
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. -
11
kubectl-aliases
Programmatically generated handy kubectl aliases
kubectl-aliases is a small but extremely handy project that generates hundreds of shell aliases for kubectl so you no longer have to type long commands and flags repeatedly. It ships a prebuilt .kubectl_aliases file for Bash/Zsh, plus variants for Fish and Nushell, which you drop into your home directory and source from your shell config. The aliases are programmatically generated from permutations of common verbs, resources, flags, and options, so you get short forms like kgpo for kubectl... -
12
Bloom filters
Go package implementing Bloom filters
A Bloom filter is a concise/compressed representation of a set, where the main requirement is to make membership queries; i.e., whether an item is a member of a set. A Bloom filter will always correctly report the presence of an element in the set when the element is indeed present. A Bloom filter can use much less storage than the original set, but it allows for some 'false positives': it may sometimes report that an element is in the set whereas it is not. When you construct, you need to... -
13
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. ... -
14
XEROX SIGMA 7 XPL Compiler
XPL Compiler for the XEROX SIGMA 7
XPL Compiler for the XEROX SIGMA 7 written at Lawrence Livermore Labs in 1971. This compiler ran under the GORDO Operating System. This project includes a SLR(K) grammar analyzer written by Frank DeRemer. Both the compiler and grammar analyzer have been ported to run under UNIX. -
15
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:... -
16
opk
Misc. Open Source by OPWvH-K
Miscellaneous stuff written by Oscar Westra van Holthe - Kind. See the individual projects for licensing details. -
17
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 tools make managing a vast number of clients comfortable. The integration of existing clients (with .deb-based distributions) into the system is possible, too. ... -
18
Koarse Grind (formerly Coarse Grind)
Test Automation framework intended for coarse-grained testing
Koarse Grind has been rewritten in Kotlin (hence the 'K'). It's new home is here: https://github.com/william-hood/koarse-grind-kotlin __________________________________ Test Automation framework for Kotlin/Java with an integrated web-based user interface. It is intended for larger-grained testing of an installed & configured product, rather than unit testing. -
19
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... -
20
fastMRI
A large open dataset + tools to speed up MRI scans using ML
fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data... -
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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
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22
whiteboxgui
An interactive GUI for WhiteboxTools in a Jupyter-based environment
...Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. WhiteboxTools also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; etc. -
23
Beautiful Web Fonts in Various Languages
Including Demo Example Webpage & Professional Documenting Application
Languages Covered : Arabic, Bengali-Assamese, Devanagari ( Marathi, Pāḷi, Sanskrit, Hindi, Boro, Nepali, Sherpa, Prakrit, Apabhramsha, Awadhi, Bhojpuri, Braj, Bhasha, Chhattisgarhi, Haryanvi, Magahi, Nagpuri, Rajasthani, Bhili, Dogri, Kashmiri, Konkani, Sindhi, Nepal Bhasa, Mundari, and Santali. ), Gujarati, Hebrew, Japanese, JapaneseHW, Korean (K), KoreanHW, SimplifiedChinese (SC), SimplifiedChineseHW, TraditionalChinese (TC), TraditionalChineseHK, TraditionalChineseHKHW, TraditionalChineseHW, Kannada, Khmer, Main Latin, Cyrillic, Greek, Malayalam, Myanmar, Oriya, Punjabi, Punjabi-Gurmukhi, Sinhala, Tamil, Telugu, Thai, Tibetan, Urdu, Cyrillic (ext), Greek (ext), Latin (ext), Vietnamese Please extract this 2.5 GB ZIP file and follow the instructions in the "1. ... -
24
Ofront+
Oberon family of languages to C translator for ARM, x64 and x86 archit
Ofront+ is a tool that translates programs in Oberon dialects into semantically equivalent C programs. Full error analysis is performed on the Oberon input program and in case of no errors up to three files are generated as output. Ofront+ does not invoke the C compiler or linkage editor. This may be done in separate shell scripts or make files and is inherently dependent on the C compiler and linkage editor being used. Although normally not read by the user, the C code generated by... -
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krangl
krangl is a {K}otlin DSL for data w{rangl}ing
krangl is a {K}otlin library for data w{rangl}ing. Implementing a grammar of data manipulation using a modern functional-style API, allows filtering, transforming, aggregating, and reshaping tabular data. krangl is heavily inspired by the amazing dplyr for R. krangl is written in Kotlin, excels in Kotlin, but emphasizes as well on good java-interop.
