visualization packages for vector space
Semantic search using TF-IDF vector space — cosine similarity, intent matching, document similarity.
A WebAssembly implementation of the k-means clustering algorithm for color quantization and general vector-space clustering.
No description provided.
A library that provides vectors, lines and planes in a three-dimensional vector space
this module is using for calculating the cosine similarity and vector space model using tfidf
Extensible mathematical vector-space utilities
An implementation of the tf-idf vector space model for keyword search
this module is using for calculating the cosine similarity and vector space model using tfidf
Parse and stringify space separated tokens
Creates a term vector from tokenized text.
Built-in support for popular icon fonts and the tooling to create your own Icon components from your font and glyph map. This is a wrapper around react-native-vector-icons to make it compatible with Expo.
Curated collection of data structures for the JavaScript/TypeScript.
Parses vector tiles
micromark factory to parse markdown space (found in lots of places)
Collapse white space
Isomorphic storage client for Supabase.
PostgreSQL pgvector extension pack for Prisma Next.
Serialize mapbox vector tiles to binary protobufs in javascript.
Slice GeoJSON data into vector tiles efficiently
Serialize mapbox vector tiles to binary protobufs in javascript.
Light multi-platform disk space checker without third party for Node.js
Slice GeoJSON data into vector tiles efficiently
JSON without touching any globals
Generic vector space trait for compatibility across various libraries
Aitchison-simplex vector-space algebra on compositions: closure, perturbation, powering, centering and Aitchison inner product — scikit-bio skbio.stats.composition {closure,perturb,perturb_inv,power,centralize,inner} equivalent
vector database: base Lance storage
Sparse & dense vectors for use in high dimensional vector spaces.
Access components of generic vector types
Secret-sharing primitives (Shamir, Blakley, ramp, VSS, CRT, visual, etc.) implemented directly from the original papers with no external dependencies.
Provides the dot product trait and auto implements the inner space trait, which contains a bunch of useful functions for working with vectors
OptiRS Neural Architecture Search and hyperparameter optimization
A library for creating and computing interpolations, extrapolations and smoothing of generic data points.
Simple extensible collision management
Simple, dimension generic vector math
Generic spatial transforms and movement, built on geometric algebra traits
A Ruby library for treating multidimensional values as elements of a vector space.
A Ruby library for treating multidimensional values as elements of a vector space
A simple vector space search engine with tf*idf ranking.
SimpleSearch is a simple vector space text search engine.
A collection of useful Mathematical and Vector tools in 2D space
This little gem calculates the entropy and ( the cardinality) of a finite probability space, defined by a probability vector; and of a finite probability metric space, defined by a probability vector and metric function. Requires ruby 1.9.x
Tokkens makes it easy to apply a vector space model to text documents, targeted towards with machine learning. It provides a mapping between numbers and tokens (strings)
GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training is performed on aggregated global word-word co-occurrence statistics from a corpus, and the resulting representations showcase interesting linear substructures of the word vector space. This is a pure Ruby implementation of GloVe utilizing GSL.
A Numeric-like vector space implementation for Ruby. Perform arithmetic on heterogeneous objects, calculate norms and dot products, get hash-like access to components, and seamlessly interoperate with core numbers. Zero dependencies, pure Ruby.
Newtonian physics gives a way to predict the future state of a system of massive objects in a Euclidean space. This gem provides a library of classes such as Point, Vector, Force. This gem enables a system built from these classes to be evolved forward in time according to Newton's laws of motion.
Proper related posts plugin for Jekyll - uses document correlation matrix on TF-IDF (optionally with Latent Semantic Indexing). Each document is tokenized and stemmed, every word found is treated as keyword for analysis (except for some stop words). TF-IDF matrix for the whole site is calculated (including extra provided weights), then if given accuraccy is lower than 1.0, LSI algorithm is used to compute new simplified vector space. Document correlation matrix is created using dot product of the matrix and its transpose. For each of the post' related documents are inserted into priority queue (sorted by score from document correlation matrix), assuming the score is greater than minimal required score. Selected few bests related posts are retrieven from the queue. Liquid template for each post is rendered and <related-posts /> is replaced with the outcomes of algorithm.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.