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dsp.js

Digital Signal Processing for Javascript

dspfilters

A Collection of Useful C++ Classes for Digital Signal Processing

dssim

DSSIM C implementation

duckhunt-js

DuckHunt ported to JS and HTML5 with a level creator

duktape

Duktape - embeddable Javascript engine with a focus on portability and compact footprint

duration

Duration is an application for designing change over time

dxr

An intelligent source code browser

dygraphs

Interactive visualizations of time series using JavaScript and the HTML canvas tag

dynomite

A generic dynamo implementation for different k-v storage engines

earcut

The fastest and smallest JavaScript polygon triangulation library for your WebGL apps

earcut.hpp

Fast, header-only polygon triangulation

earth

a project to visualize global weather conditions

easeljs

The Easel Javascript library provides a full, hierarchical display list, a core interaction model, and helper classes to make working with the HTML5 Canvas element much easier.

eases

a grab-bag of modular easing equations

easy6502

easyagal

EasyAGAL is an open source ActionScript library that simplifies coding assembly language shaders. Advantages include: Code completion and hinting, easier-to-read code, macro libraries -- including trigonometry functions like atan2(), color blending formulas from Photoshop, and more -- ready to use in your own shaders.

easyexif

Tiny ISO-compliant C++ EXIF parsing library, third-party dependency free.

easygoogle

Simple wrapper library for Google APIs

echoplexus

Socket.io powered chat, JavaScript REPL, whiteboard, and WebRTC calls

echoprint-codegen

Codegen for Echoprint

echoprint-server

Server components for Echoprint

ecmascript_simd

SIMD numeric type for EcmaScript

economicintelligence

The project focused on the use of public data to assess the economic situation in the country based on the state of the stock market and national means of payment, in particular - of the national currency. As sources are used: Open data Ministry of Finance of the Russian Federation These Moscow Exchange Google Finance Data Technologies used: Backend: Databases (relational) - Microsoft SQL Server 2014 Databases (multivariate) models DataMining, OLAP-cube - Microsoft Analysis Services 12.0 Веб-сервер - Windows Server 2012 / Internet Information Services Самописный ASP.NET HTTP Restful интерфейс для взаимодействия с Frontend ETL (загрузка и пре-процессинг данных, управление обновлением данных) SQL Server Integration Services 2014 (разработка в Visual Studio 2013, SSDT) Frontend: AngularJS ChartJS Twitter Bootstrap These were chosen so that the detail (granularity) in the set is not less than 1 day. The result has been created and filled with data analytic repository (Kimball model, topology - star), which was used to build a multi-dimensional databases and OLAP-based cubes on it, as well as models of analysis of data on two main algorithms: Microsoft Time Series, Microsoft Neural Network . To ensure interoperability frontend and backend server for backend-server was set up HTTP-Restful interface JSON-issuing documents in the form of finished sets. The project includes two main areas: Intelligent visualization of open data Analysis of open data and the construction of forecasts based on them Intelligent visualization involves the use of MDX-queries to the OLAP-cube, followed by depression (drilldown) in the data, the system allows the user to quickly find the "weak points" of the economy, as part of the data collected. To predict the time a standard mix of algorithms ARTXP / ARIMA, without the use of queries involving cross-prediction (but it is possible to enroll in the system correct data). These algorithms have been tested primarily on foreign exchange rates (US dollar) and the assets of banks included in the special list of Ministry of Finance. In addition, for assets shows the different customization options algorithms - a long-term, short-term and medium-term (balanced) plan. Assessing the impact of oil prices and foreign currency exchange rate for the total market capitalization was conducted on a sample of the data collected: companies with a total market capitalization of 100 to 500 million rubles, present in the market during 2013-2015 Analytical server builds the neural network receiving the input exchange rates, companies, the weighted average share price, total capitalization of the company and the price of oil to requests received models give the opportunity to evaluate the growth rate of \ fall (if at all) the company's capitalization at historical exchange rates and / or the cost of oil. Built a system can expand to include new indicators, which will significantly increase the accuracy of forecasting.

edgit

Edit Github repos and run them in your browser.

edited

editor

GUI editor

editor-framework

A framework lets you easily write professional IDE like desktop tools just in HTML5 and io.js

editr.js

HTML, CSS and JavaScript playground

edx-dl

A simple tool to download video lectures from edx.org.

eec

Electronics Engineering Calculator