Javascript Libraries and Links

Web Client Libraries and Frameworks
jQuery
jQuery is a fast and concise JavaScript Library that simplifies HTML document traversing, event handling, animating, and Ajax interactions for rapid web development.

Underscore.js
Underscore is a utility-belt library for JavaScript that provides a lot of the functional programming support that you would expect in Prototype.js (or Ruby), but without extending any of the built-in JavaScript objects. It's the tie to go along with jQuery's tux.

Modernizr
Modernizr is your starting point for making the best websites and applications that work exactly right no matter what browser or device your visitors use.

Knockout.js
Simplify dynamic JavaScript UIs by applying the Model-View-View Model (MVVM)

Backbone.js
Backbone supplies structure to JavaScript-heavy applications by providing models with key-value binding and custom events, collections with a rich API of enumerable functions, views with declarative event handling, and connects it all to your existing application over a RESTful JSON interface.


JS and CSS Toolkits
Google Libraries API
The Google Libraries API is a content distribution network and loading architecture for the most popular, open-source JavaScript libraries.

CoffeeScript
CoffeeScript is a little language that compiles into JavaScript. Underneath all those awkward braces and semicolons, JavaScript has always had a gorgeous object model at its heart. CoffeeScript is an attempt to expose the good parts of JavaScript in a simple way. Also see: dart

lesscss
LESS extends CSS with dynamic behavior such as variables, mixins, operations and functions. LESS runs on both the client-side (IE 6+, Webkit, Firefox) and server-side, with Node.js and Rhino.

twitter bootstrap
Simple and flexible HTML, CSS, and Javascript for popular user interface components and interactions.

requirejs.org
JavaScript file and module loader. It is optimized for in-browser use, but it can be used in other JavaScript environments, like Rhino and Node. Using a modular script loader like RequireJS will improve the speed and quality of your code.


JS InfoVis Libraries
Processing.js
Processing.js is the sister project of the popular Processing visual programming language, designed for the web. Processing.js makes your data visualizations, digital art, interactive animations, educational graphs, video games, etc. work using web standards and without any plug-ins.

d3.js
D3.js is a small, free JavaScript library for manipulating documents based on data and visualization framework. (From the authors of the now inactive protovis.)

Flot
Flot is a pure Javascript plotting library for jQuery. It produces graphical plots of arbitrary datasets on-the-fly client-side.

arborjs
Arbor is a graph visualization library built with web workers and jQuery. Rather than trying to be an all-encompassing framework, arbor provides an efficient, force-directed layout algorithm plus abstractions for graph organization and screen refresh handling.

Raphaël
Raphaël is a small JavaScript library that should simplify your work with vector graphics on the web. If you want to create your own specific chart or image crop and rotate widget, for example, you can achieve it simply and easily with this library.


JS Math Libraries
MathJax
MathJax is an open source JavaScript display engine for mathematics that works in all modern browsers.

jStat
jStat is a statistical library written in JavaScript that allows you to perform advanced statistical operations without the need of a dedicated statistical language (i.e. MATLAB or R).


On the Radar
Stripe.js
Stripe.js lets you build your own payment forms while still avoiding most PCI requirements.  Credit cards go directly to Stripe's secure environment, and never hit your servers.

three.js
Javascript 3D Engine. The aim of the project is to create a lightweight 3D engine with a very low level of complexity.

speak.js
Enables text-to-speech on the web using only JavaScript and HTML5. A port of the eSpeak speech synthesizer from C++ to JavaScript using Emscripten. Online demo: http://syntensity.com/static/espeak.html


Blog Posts Etc
Knockout.js vs. Backbone.js
Introducing Knockout, a UI library for JavaScript
A re-introduction to JavaScript (mozilla.org)
JavaScript for C# developers: writing a library
20 Fresh JavaScript Data Visualization Libraries

R Packages

Here is a list of R packages that I find useful:

ggplot2 - is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and none of the bad parts. (Sep 2011)

caret - is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for: data splitting, pre-processing, model tuning using resampling, variable importance estimation. (short for Classification And REgression Training) (Sep 2011)

randomForest - Classification and regression based on a forest of trees using random inputs. (Dec 2011)

ada - Performs discrete, real, and gentle boost under both exponential and logistic loss on a given data set. The package ada provides a straightforward, well-documented, and broad boosting routine for classification, ideally suited for small to moderate-sized data sets. (Dec 2011)

gbm - Generalized Boosted Regression Models.  This package implements extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, quantile regression, logistic, Poisson, Cox proportional hazards partial likelihood, and AdaBoost exponential loss. (Dec 2011)

dummies - Create dummy/indicator variables flexibly and efficiently.  Expands factors, characters and other eligible classes into dummy/indicator variables.

multicore - Overcome R's inefficient CPU usage.  This package provides a way of running parallel computations in R on machines with multiple cores or CPUs. Jobs can share the entire initial workspace and it provides methods for results collection.

List of Data Mining / Forcasting Competitions

Kaggle
http://www.kaggle.com/Competitions

TunedIT Solutions
http://tunedit.org/challenges/

Causality Workbench (none current as of Aug 2011)
http://www.causality.inf.ethz.ch/home.php

DARPA's Shredder Challenge (document reconstruction)
Closes December 5, 2011
http://www.shredderchallenge.com/

1st International Competition of Time Series Forecasting
Closes 10th of January 2012
http://www.caos.inf.uc3m.es/~jperalta/ICTSF/

if you know of any more sites offering data mining / forecasting / machine learning competitions please leave a comment!  Thanks.

Free Utilities for a New Machine

NOTE: this is a work in progress, links coming...


Apps

Chrome

Firefox

irfanview

FoxitReader

mRemote

FileZilla

foobar2000

vlc

Skype

System

Wizmouse (scrolling fix) v1.0.0.5.exe

puretext20_x86.zip

notepad++

7zip

Launchy

VirtualBox + Ubuntu

Xming Xserver

putty

SysinternalsSuite

www.magiciso.com/tutorials/miso-magicdisc-overview.htm

ImgBurn

TreeSizeFree

Generic Development Tools

Reflector / JustDecompile www.telerik.com/products/decompiling.aspx

DiffMerge

WinMerge

Expresso Regex

XPathBuilder v2.0.0.4

LINQPad

Screen Ruler

Tortoise SVN

Specific Development Tools

Eclipse

Python

MonoDevelop


Commercial Software

Visual Studio (2008 and 2010)

ReSharper

SQL Server Management Studio

Redgate SQL Compare adn SQL Data Compare

Microsoft Office

Windows hosted virtual private server (VPS) set up

In early 2010 I migrated my websites from shared web host that had begun to suck to a virtual private server (VPS) provided by Web24.

I did this for performance reasons as the shared web host had degraded over the course of several years, and additionally I wanted control over what was installed on the machine just like when at work.

Due to low traffic and budget constraints I'm running the VPS as a web server (IIS), DB server (SQL Server Express, and MySQL) and an SMTP server.  Here are my notes regarding the server installation and configuration so I can do it again fairly quickly if needed.

NOTE: these details were accurate at March 2010, newer versions and service packs are probably available now.

VPS Configuration
Windows Server 2003 R2, 64 bit
IIS 6
1GB RAM
10GB disk space
Parallels Power Panel
Full remote desktop access

General Utilities Installed
7zip, notepad++, Winmerge and Sysinternals Suite

Web Platform Installer
Used the WPI to install: .NET FW 2.0 .NET FW 3.5SP1, MVC 2.0

Database Servers
MySQL:

• MySQL Community Server
• MySQL GUI Tools 5
• Install guide: Install and Configure MySQL 5 on Windows (non-strict mode)

SQL Server 2008 Express:

• Windows Installer 4.5 Redistributable x64  (Required for SQL 2008)
• Windows PowerShell 1.0 x64 (Required for SQL 2008)
• Microsoft® SQL Server® 2008 Express with Tools
• SQL Server 2008 Service Pack 1

SMTP Mail Server

hMailServer:

• hMailServer Download
• Guide: Setting up your own email server with hMailServer
• Guide: Quick set up
• Docs: Configuration tutorial
• Finally, testing for Anonymous Relay

PHP5 on IIS6

• Download latest PHP For Windows (following notes based on v5.3.x)
• If you are using PHP with IIS you should use the VC9 versions of PHP (Microsoft 2008 C++ Runtime (x86) or the Microsoft 2008 C++ Runtime (x64)  installed)
• Since PHP v5.3 uses FastCGI we should use the non-thread safe version of PHP (php-5.3.2-nts-Win32-VC9-x86.zip)
• Download FastCGI for IIS (Note: can use FastCGI x64 with php x86 ok, see this thread: FastCGI x64 glitch)
• Guide: Installing FastCGI and PHP for IIS 6.0
• Guide: Installing PHP 5 on IIS in 5 simple steps (v5.2 only)
• Guide: How to install PHP 5.x on Windows Server 2003 with IIS 6
• Windows Server x64 specific config: PHP on 64 bit Windows (fixes "%1 is not a valid Win32 application" issue by allowing IIS to run 32 bit apps.  Here is the command: cscript %SYSTEMDRIVE%\inetpub\adminscripts\adsutil.vbs SET W3SVC/AppPools/Enable32bitAppOnWin64 1

Web Mail

roundcube (PHP application):

• Download roundcube
• Guide: Install and configure RoundCube Webmail on IIS
• Guide: Install Roundcube with IIS6 and hMs internal DB
• Guide: Installation
• Guide: Configuration

Yep, that's it, too easy really.  Overall I'm pretty happy with Web24 - faster than the old shared hosting, and (almost) complete control over the environment. Only downside is a few more sysadmin tasks.

Next thing to do is switch to Server 2008 with IIS 7.

Entity Framework and LINQ2SQL Links

EF
Migrating from LINQ to SQL to Entity Framework: Eager Loading
http://blogs.msdn.com/adonet/archive/2008/10/07/migrating-from-linq-to-sql-to-entity-framework-eager-loading.aspx

Known Issues and Considerations in LINQ to Entities
http://msdn.microsoft.com/en-us/library/bb896317.aspx


LINQ2SQL

Linq to SQL DataContext Lifetime Management (Rick Strahl)

http://www.west-wind.com/weblog/posts/246222.aspx

Python Libraries

Here are some useful Python libraries I've been using for conducting and visualising experiments in machine learning, forecasting and statistical learning. It is updated as I discover new libraries/applications.
Last updated April 2013.

Libraries

numpy - Numerical Python - Numerical Python adds a fast and sophisticated array facility to the Python language. NumPy is the most recent and most actively supported package.

scipy - Scientific Library for Python - SciPy is package of tools for science and engineering for Python. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.

matplotlib - matplotlib tries to make easy things easy and hard things possible. You can generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc, with just a few lines of code

PyBrain -  Python-Based Reinforcement Learning, Artificial Intelligence and Neural Network Library. PyBrain is a modular Machine Learning Library for Python. Its goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms.

nltk - Natural Language Toolkit — is a suite of open source Python modules, data and documentation for research and development in natural language processing.

PIL - Python Imaging Library adds image processing capabilities to your Python interpreter.

mlpy - Machine Learning PYthon - high-performance Python library for predictive modeling. Makes extensive use of  NumPy to provide fast N-dimensional array manipulation and easy integration of C code. The GNU Scientific Library ( GSL) is also required. It provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification, regression and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping.

networkx - High productivity software for complex networks - creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

neurolab - a simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework to create and explore other networks. Pure python + numpy.
Includes: Single layer perceptron, Multilayer feed forward perceptron, Competing layer (Kohonen Layer), Learning Vector Quantization (LVQ), Elman Recurrent network, Hopfield Recurrent network. (Sep 2011)
[Note: after using this library I prefer PyBrain since it feels more stable and better documented. However neurolab has a similar api to the MATLAB NN Toolbox]

scikits.learn - Easy-to-use and general-purpose machine learning in Python. Python module integrating classic machine learning algorithms in the tightly-knit world of scientific Python packages (numpy, scipy, matplotlib).  It aims to provide simple and efficient solutions to learning problems that are accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering. Part of SciKits. (Aug 2011)

scikits.* - SciKits (short for SciPy Toolkits), are add-on packages for SciPy, hosted and developed separately from the main SciPy distribution. All SciKits are available under the 'scikits' namespace.
Selected examples that have recent updates and look maintained: (Sep 2011)

• datasmooth - data smoothing package
• learn -  machine learning and data mining
• statsmodels - statistical computations and models for use with SciPy
• timeseries - time series manipulation

Tablib - allows you to import, export, and manipulate tabular data sets. Advanced features include, segregation, dynamic columns, tags & filtering, and seamless format import & export. (Sep 2011)

pyneurgen - Python Neural Genetic Hybrids.  This software provides libraries for use in Python programs to build hybrids of neural networks and genetic algorithms and/or genetic programming. (Sep 2011)

pyml - machine learning in Python. PyML is an interactive object oriented framework for machine learning, it focuses on SVMs and other kernel methods.
Features:
Classifiers: support vector machines, nearest neighbor, ridge regression
Multi-class methods (one-against-rest and one-against-one)
Feature selection (filter methods, RFE)
Model selection
Preprocessing and normalization
Syntax for combining classifiers
Classifier testing (cross-validation, error rates, ROC curves)
(Sep 2011)

Pandas - pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.  R users will be pleased to find this library adopts some of the best concepts of R, like the foundational DataFrame (April 2013)

PyTables - PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data. PyTables is built on top of the HDF5 library, using the Python language and the NumPy package. (April 2013)

gensim - realize unsupervised semantic modelling from plain text.  Useful to determine similarity between pairs of documents.  Includes Latent Sematic Analysis and Latent Dirichlet Allocation (April 2013)

ramp - Ramp is a python package for rapid machine learning prototyping. It provides a simple, declarative syntax for exploring features, algorithms and transformations quickly and efficiently. At its core it’s a unified pandas-based framework for working with existing python machine learning and statistics libraries (scikit-learn, rpy2, etc.) (April 2013)

Statsmodels - Statsmodels is a Python module that allows users to explore data, estimate statistical models, and perform statistical tests. An extensive list of descriptive statistics, statistical tests, plotting functions, and result statistics are available for different types of data and each estimator. (April 2013)

Blaze - Blaze is the next generation of NumPy, Python’s extremely popular array library. Blaze is designed to handle out-of-core computations on large datasets that exceed the system memory capacity, as well as on distributed and streaming data. (April 2013)



Applications

IPython - IPython provides a rich toolkit to help you make the most out of using Python interactively. Its main components are:
Powerful interactive Python shells (terminal- and Qt-based).
Support for interactive data visualization and use of GUI toolkits.
Flexible, embeddable interpreters to load into your own projects.
Tools for high level and interactive parallel computing.

Orange - Open source data visualization and analysis for novice and experts. Data mining through visual programming or Python scripting. Components for machine learning. Extensions for bioinformatics and text mining. Packed with features for data analytics.