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Commons Math is a library of lightweight, self-contained mathematics and statistics components addressing the most common problems not available in the Java programming language. it has support for Linear Algebra, Probability Distributions, Numerical Algebra, Statistics, Transform methods, Least Square etc.

math math-library mathematics statistics algebraA statistics package with many functions missing from the Golang standard library. See the CHANGELOG.md for API changes and tagged releases you can vendor into your projects.Protip: go get -u github.com/montanaflynn/stats updates stats to the latest version.

statistics math data analyticsThe Accord.NET project provides machine learning, statistics, artificial intelligence, computer vision and image processing methods to .NET. It can be used on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile.

machine-learning framework c-sharp nuget visual-studio statistics unity3d neural-network support-vector-machines computer-vision image-processing ffmpegA network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

stats statistics aggregator data-aggregatorAnomalyDetection is an open-source R package to detect anomalies which is robust, from a statistical standpoint, in the presence of seasonality and an underlying trend. The AnomalyDetection package can be used in wide variety of contexts. For example, detecting anomalies in system metrics after a new software release, user engagement post an A/B test, or for problems in econometrics, financial engineering, political and social sciences.

anomaly-detection fraud-detection statisticsScientific and statistical computing in JavaScript.

science statistics mathematicsSeaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.Online documentation is available at seaborn.pydata.org. Installation requires numpy, scipy, pandas, and matplotlib. Some functions will optionally use statsmodels if it is installed.

data-visualization visualization statisticsDetermine in realtime what's happening inside your node process from the terminal. No need to instrument code to get the deets. Also splits stderr/stdout to help spot errors sooner.NOTE: This module isn't designed for production use and should be limited to development environments.

nodejs telemetry monitoring dashboard terminal realtime statisticsTurf is a JavaScript library for spatial analysis. It includes traditional spatial operations, helper functions for creating GeoJSON data, and data classification and statistics tools. Turf can be added to your website as a client-side plugin, or you can run Turf server-side with Node.js (see below).Download the minified file, and include it in a script tag. This will expose a global variable named turf.

algorithm computational-geometry geojson turf gis geo geojs geospatial geography geometry map contour centroid tin extent grid polygon line point area analysis statistics stats midpoint plane quantile jenks sampleThe probability and statistics cookbook contains a succinct representation of various topics in probability theory and statistics. It provides a comprehensive mathematical reference reduced to its essence, rather than aiming for elaborate explanations. Feel encouraged to extend the cookbook by forking it and submitting pull requests.

probability statistics cheatsheet cookbookR is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.

language programming-language statistical-language statisticsMiller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON. With Miller, you get to use named fields without needing to count positional indices, using familiar formats such as CSV, TSV, JSON, and positionally-indexed.

data-processing data-cleaning csv csv-files csv-format csv-reader streaming-data streaming-algorithms tsv json json-data data-reduction data-regression statistics statistical-analysis devops devops-tools tabular-data command-line command-line-toolsboltons should be builtins. Full and extensive docs are available on Read The Docs. See what's new by checking the CHANGELOG.

utilities cache data-structures statistics data-science file queue json recursiveLocal git statistics including GitHub-like contributions calendars.

contributions-calendar gitstats calendar statistics git stats github cliNormally when rolling a 4 sided die, you would have a 25% chance of rolling any given face, at any time. If you rolled a 4, three times in a row it doesn't make it any less probable of happening the next time. Further, a 1 is not "more likely" because "it hasn't been rolled in a while". This library breaks that standard rule.

dice fallacy roll statistics gambler-fallacy terrible-idea random gambler monte carloMath literacy, including proficiency in Linear Algebra and Statistics,is a must for anyone pursuing a career in data science. The goal of this workshop is to introduce some key concepts from these domains that get used repeatedly in data science applications. Our approach is what we call the “Hacker’s way”. Instead of going back to formulae and proofs, we teach the concepts by writing code. And in practical applications. Concepts don’t remain sticky if the usage is never taught. The focus will be on depth rather than breadth. Three areas are chosen - Hypothesis Testing, Supervised Learning and Unsupervised Learning. They will be covered to sufficient depth - 50% of the time will be on the concepts and 50% of the time will be spent coding them.

machine-learning linear-algebra statistics calculusEdward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets. Edward fuses three fields: Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on top of TensorFlow. It enables features such as computational graphs, distributed training, CPU/GPU integration, automatic differentiation, and visualization with TensorBoard.

bayesian-methods deep-learning machine-learning data-science tensorflow neural-networks statistics probabilistic-programmingUsing this package you can easily retrieve data from Google Analytics. Most methods will return an \Illuminate\Support\Collection object containing the results.

laravel analytics google statisticsPlease cite our JMLR paper [bibtex]. Some parts of the package were created as part of other publications. If you use these parts, please cite the relevant work appropriately. An overview of all mlr related publications can be found here.

machine-learning data-science tuning cran r-package predictive-modeling classification regression statistics r survival-analysis imbalance-correction tutorial mlr learners hyperparameters-optimization feature-selection multilabel-classification clustering stackingTokei is a program that displays statistics about your code. Tokei will show number of files, total lines within those files and code, comments, and blanks grouped by language. Tokei is very fast, check out our comparison document to see how Tokei's speed compares to others.

tokei cloc badge statistics code cli
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