Return a natural number.
Generate a random natural number with Chance.js.
Compare strings containing a mix of letters and numbers in the way a human being would in sort order.
Generate a random natural number with Chance.js.
Lightweight and performant natural sorting of arrays and collections by differentiating between unicode characters, numbers, dates, etc.
Compare strings containing a mix of letters and numbers in the way a human being would in sort order.
Compare alphanumeric strings the same way a human would, using a natural order algorithm
Check if a value is a natural number
Generate random numbers from various distributions.
General natural language (tokenizing, stemming (English, Russian, Spanish), part-of-speech tagging, sentiment analysis, classification, inflection, phonetics, tfidf, WordNet, jaro-winkler, Levenshtein distance, Dice's Coefficient) facilities for node.
Fastest random ID and random string generation for Node.js
TypeScript definitions for d3-random
various machine learning routines for node
URL and cookie safe UIDs
Use the random function in CSS
Generate a cryptographically strong random string
An alias package for `crypto.randomBytes` in Node.js and/or browsers
retext plugin to serialize prose
Random utility functions for ethers.
Compare strings in a natural order
A Pulumi package to safely use randomness in Pulumi programs.
retext plugin to parse Latin-script prose
A small implementation of `crypto.getRandomValues` for React Native. This is useful to polyfill for libraries like [uuid](https://www.npmjs.com/package/uuid) that depend on it.
Provides functions for detecting if the host environment supports the WebCrypto API
Generate random numbers that adhere to Benford's Law
People friendly readable UUIDs
The polymorphous password generator.
This Ruby gem leverages Machine Learning(ML) techniques to make predictions(forecasts) and classifications in various applications. It provides capabilities such as predicting next month's billing, forecasting upcoming sales orders, identifying patient's potential findings(like Diabetes), determining user approval status, classifying text, generating similarity scores, and making recommendations. It uses Python3 under the hood, powered by popular machine learning techniques including NLP(Natural Language Processing), Decision Tree, K-Nearest Neighbors and Logistic Regression, Random Forest and Linear Regression algorithms.
A Ruby library for data obfuscation that: - Preserves original data format and structure as much as possible - Supports numbers (including IP-like sequences), dates, and text - Maintains text structure while replacing content with meaningless but natural-looking words in English and Russian - Maintains data type consistency and decimal precision - Offers seeded randomization for reproducible results - Handles various number formats (leading zeros, separators) - Provides configurable options (unsigned mode, format preservation) Note: Individual obfuscator instances are not thread-safe. For concurrent operations, create separate instances per thread.
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