Javascript Tools and Testing
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The Shogun Machine Learning Toolbox
The Shogun Machine Learning Toolbox Heiko Strathmann, Gatsby Unit, UCL London Open Machine Learning Workshop, MSR, NY August 22, 2014 A bit about Shogun I Open-Source tools for ML problems I Started 1999 by SÖren Sonnenburg & GUNnar Rätsch, made public in 2004 I Currently 8 core-developers + 20 regular contributors I Purely open-source community driven I In Google Summer of Code since 2010 (29 projects!) Ohloh - Summary Ohloh - Code Supervised Learning Given: x y n , want: y ∗ x ∗ I f( i ; i )gi=1 j I Classication: y discrete I Support Vector Machine I Gaussian Processes I Logistic Regression I Decision Trees I Nearest Neighbours I Naive Bayes I Regression: y continuous I Gaussian Processes I Support Vector Regression I (Kernel) Ridge Regression I (Group) LASSO Unsupervised Learning Given: x n , want notion of p x I f i gi=1 ( ) I Clustering: I K-Means I (Gaussian) Mixture Models I Hierarchical clustering I Latent Models I (K) PCA I Latent Discriminant Analysis I Independent Component Analysis I Dimension reduction I (K) Locally Linear Embeddings I Many more... And many more I Multiple Kernel Learning I Structured Output I Metric Learning I Variational Inference I Kernel hypothesis testing I Deep Learning (whooo!) I ... I Bindings to: LibLinear, VowpalWabbit, etc.. http://www.shogun-toolbox.org/page/documentation/ notebook Some Large-Scale Applications I Splice Site prediction: 50m examples of 200m dimensions I Face recognition: 20k examples of 750k dimensions ML in Practice I Modular data represetation I Dense, Sparse, Strings, Streams, ... I Multiple types: 8-128 bit word size I Preprocessing tools I Evaluation I Cross-Validation I Accuracy, ROC, MSE, .. -
Quickly Documentation Release 0.1
Quickly Documentation Release 0.1 Michael Spencer March 28, 2016 Contents 1 Offline Reading 3 1.1 Tutorial..................................................3 1.2 QMLify Transpiler............................................5 1.3 Core JS Modules.............................................5 1.4 Distributing your Module........................................8 2 Indices and tables 11 i ii Quickly Documentation, Release 0.1 Quickly is a build tool and QML module with provides an NodeJS-like ES6 environment for Javascript used in QML. The goal of the project is to allow you to write awesome modern ES6 Javascript taking advantage of classes, decorators, arrow functions, and best of all, many of the vast array of NPM packages available using the standard ES6 module imports. You can then take that code and use in directly from QML, just as you would with plain, old, QML-specific Javascript. You can even build a library using ES6 and NPM packages, and then distribute that as a standard QML module or QPM package for other developers to use in regular QML or QML-specific Javascript. For those who would prefer to stick with standard QML-specific Javascript, you can also do that and still use the Quickly library, which gives you promises, the fetch API, and many polyfills. This is great for longtime QML devel- opers or existing projects that just want to drop in some easy-to-use features from modern JS core libraries. Tutorial A quick guide to get you up and running with Quickly. QMLify Transpiler How to use qmlify, the Quickly transpiler. Core JS Modules How to use the core JS modules. Distributing your Module Distributing your awesome new module for other developers to use. -
Webpack Cheatsheet
12/25/18, 655 PM Page 1 of 1 ! Edit Webpack cheatsheet — Proudly sponsored by — Airbrake.io Full-stack error tracking & analytics for Python developers. Try it Free! ethical ads via CodeFund This is a very basic “getting started with Webpack” guide for use with Webpack v3. This doesnʼt cover all features, but it should get you started in understanding the config file format. Basic config webpack.config.js module.exports = { context: __dirname, entry: 'src/app.js', output: { path: __dirname + '/public', filename: 'app.js' } } Terminal npm install --save-dev webpack webpack build webpack -- -p build production webpack -- --watch compile continuously This compiles src/app.js into public/app.js. (Note: you may need to use ./node_modules/.bin/webpack as a command if youʼre not invoking Webpack via npm scripts.) Multiple files webpack.config.js module.exports = { entry: { app: 'src/app.js', vendor: 'src/vendor.js' }, output: { path: __dirname + '/public', filename: '[name].js' } } This creates app.js and vendor.js. # Loaders Babel Terminal npm install --save-dev \ babel-loader \ babel-preset-env \ babel-preset-react webpack.config.js module.exports = { ··· module: { rules: [ { test: /\.js$/, exclude: /node_modules/, use: [ { loader: 'babel-loader' } ] } ] } } .babelrc { "presets": [ "env", "react" ] } Adds support for Babel. CSS Terminal npm install --save-dev \ css-loader \ style-loader webpack.config.js module.exports = { ··· module: { rules: [ { test: /\.css$/, exclude: /node_modules/, use: [ { loader: 'style-loader' }, { loader: 'css-loader' -
SWIG and Ruby
SWIG and Ruby David Grayson Las Vegas Ruby Meetup 2014-09-10 SWIG ● SWIG stands for: Simplified Wrapper and Interface Generator ● SWIG helps you access C or C++ code from 22 different languages, including Ruby SWIG inputs and outputs Ruby C extension SWIG interface file (.i) source (.c or .cxx) Simple C++ example libdavid.h: libdavid.i #include <stdio.h> %module "david" class David %{ { #include <libdavid.h> public: %} David(int x) { class David this->x = x; { } public: David(int x); void announce() void announce(); { int x; }; printf("David %d\n", x); } int x; }; Compiling Simple C++ example extconf.rb require 'mkmf' system('swig -c++ -ruby libdavid.i') or abort create_makefile('david') Commands to run: $ ruby extconf.rb # create libdavid_wrap.cxx and Makefile $ make # compile david.so $ irb -r./david # try it out irb(main):001:0> d = David::David.new(4) => #<David::David:0x007f40090a5280 @__swigtype__="_p_David"> irb(main):002:0> d.announce David 4 => nil (This example worked for me with SWIG 3.0.2 and Ruby 2.1.2.) That example was pretty simple ● All code was in a .h file ● No external libraries ● Simple data types ● No consideration of deployment ...but SWIG has tons of features C: C++: ● All ISO C datatypes ● All C++ datatypes ● Global functions ● References ● Global variables, constants ● Pointers to members ● Structures and unions ● Classes ● Pointers ● (Multiple) inheritance ● (Multidimensional) arrays ● Overloaded functions ● Pointers to functions ● Overloaded methods ● Variable length arguments ● Overloaded operators ● Typedefs ● Static members ● Enums ● Namespaces ● Templates ● Nested classes ... SWIG Typemaps ● Define custom ways to map between scripting- language types and C++ types. ● Can be used to add and remove parameters from of exposed functions. -
Npm Packages As Ingredients: a Recipe-Based Approach
npm Packages as Ingredients: a Recipe-based Approach Kyriakos C. Chatzidimitriou, Michail D. Papamichail, Themistoklis Diamantopoulos, Napoleon-Christos Oikonomou, and Andreas L. Symeonidis Electrical and Computer Engineering Dept., Aristotle University of Thessaloniki, Thessaloniki, Greece fkyrcha, mpapamic, thdiaman, [email protected], [email protected] Keywords: Dependency Networks, Software Reuse, JavaScript, npm, node. Abstract: The sharing and growth of open source software packages in the npm JavaScript (JS) ecosystem has been exponential, not only in numbers but also in terms of interconnectivity, to the extend that often the size of de- pendencies has become more than the size of the written code. This reuse-oriented paradigm, often attributed to the lack of a standard library in node and/or in the micropackaging culture of the ecosystem, yields interest- ing insights on the way developers build their packages. In this work we view the dependency network of the npm ecosystem from a “culinary” perspective. We assume that dependencies are the ingredients in a recipe, which corresponds to the produced software package. We employ network analysis and information retrieval techniques in order to capture the dependencies that tend to co-occur in the development of npm packages and identify the communities that have been evolved as the main drivers for npm’s exponential growth. 1 INTRODUCTION Given that dependencies and reusability have be- come very important in today’s software develop- The popularity of JS is constantly increasing, and ment process, npm registry has become a “must” along is increasing the popularity of frameworks for place for developers to share packages, defining code building server (e.g. -
PHP Beyond the Web Shell Scripts, Desktop Software, System Daemons and More
PHP Beyond the web Shell scripts, desktop software, system daemons and more Rob Aley This book is for sale at http://leanpub.com/php This version was published on 2013-11-25 This is a Leanpub book. Leanpub empowers authors and publishers with the Lean Publishing process. Lean Publishing is the act of publishing an in-progress ebook using lightweight tools and many iterations to get reader feedback, pivot until you have the right book and build traction once you do. ©2012 - 2013 Rob Aley Tweet This Book! Please help Rob Aley by spreading the word about this book on Twitter! The suggested hashtag for this book is #phpbeyondtheweb. Find out what other people are saying about the book by clicking on this link to search for this hashtag on Twitter: https://twitter.com/search?q=#phpbeyondtheweb Contents Welcome ............................................ i About the author ...................................... i Acknowledgements ..................................... ii 1 Introduction ........................................ 1 1.1 “Use PHP? We’re not building a website, you know!”. ............... 1 1.2 Are you new to PHP? ................................. 2 1.3 Reader prerequisites. Or, what this book isn’t .................... 3 1.4 An important note for Windows and Mac users ................... 3 1.5 About the sample code ................................ 4 1.6 External resources ................................... 4 1.7 Book formats/versions available, and access to updates ............... 5 1.8 English. The Real English. .............................. 5 2 Getting away from the Web - the basics ......................... 6 2.1 PHP without a web server .............................. 6 2.2 PHP versions - what’s yours? ............................. 7 2.3 A few good reasons NOT to do it in PHP ...................... 8 2.4 Thinking about security ............................... -
Analytic Center Cutting Plane Method for Multiple Kernel Learning
Ann Math Artif Intell DOI 10.1007/s10472-013-9331-4 Analytic center cutting plane method for multiple kernel learning Sharon Wulff · Cheng Soon Ong © Springer Science+Business Media Dordrecht 2013 Abstract Multiple Kernel Learning (MKL) is a popular generalization of kernel methods which allows the practitioner to optimize over convex combinations of kernels. We observe that many recent MKL solutions can be cast in the framework of oracle based optimization, and show that they vary in terms of query point generation. The popularity of such methods is because the oracle can fortuitously be implemented as a support vector machine. Motivated by the success of centering approaches in interior point methods, we propose a new approach to optimize the MKL objective based on the analytic center cutting plane method (accpm). Our experimental results show that accpm outperforms state of the art in terms of rate of convergence and robustness. Further analysis sheds some light as to why MKL may not always improve classification accuracy over naive solutions. Keywords Multiple kernel learning · accpm · Oracle methods · Machine learning Mathematics Subject Classification (2010) 68T05 1 Introduction Kernel methods, for example the support vector machine (SVM), are a class of algorithms that consider only the similarity between examples [1]. A kernel function S. Wulff Department of Computer Science, ETH, Zürich, Switzerland e-mail: [email protected] C. S. Ong (B) NICTA, The University of Melbourne, Melbourne, Australia e-mail: [email protected] S. Wulff, C.S. Ong k implicitly maps examples x to a feature space given by a feature map via the identity k(xi, x j) = (xi), (x j) . -
Python and Epics: Channel Access Interface to Python
Python and Epics: Channel Access Interface to Python Matthew Newville Consortium for Advanced Radiation Sciences University of Chicago October 12, 2010 http://cars9.uchicago.edu/software/python/pyepics3/ Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 Why Python? The Standard Answers Clean Syntax Easy to learn, remember, and read High Level Language No pointers, dynamic memory, automatic memory Cross Platform code portable to Unix, Windows, Mac. Object Oriented full object model, name spaces. Also: procedural! Extensible with C, C++, Fortran, Java, .NET Many Libraries GUIs, Databases, Web, Image Processing, Array math Free Both senses of the word. No, really: completely free. Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 Why Python? The Real Answer Scientists use Python. Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 All of these tools use the C implementation of Python. NOT Jython (Python in Java) or IronPython (Python in .NET): I am not talking about Jython. Why Do Scientists Use Python? Python is great. The tools are even better: numpy Fast arrays. matplotlib Excellent Plotting library scipy Numerical Algorithms (FFT, lapack, fitting, . ) f2py Wrapping Fortran for Python sage Symbolic math (ala Maple, Mathematica) GUI Choices Tk, wxWidgets, Qt, . Free Python is Free. All these tools are Free (BSD). Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 Why Do Scientists Use Python? Python is great. The tools are even better: numpy Fast arrays. matplotlib Excellent Plotting library scipy Numerical Algorithms (FFT, lapack, fitting, . ) f2py Wrapping Fortran for Python sage Symbolic math (ala Maple, Mathematica) GUI Choices Tk, wxWidgets, Qt, . -
High-Performance Language Interoperability for Scientific
High-Performance Language Interoperability for Scientific Computing through Babel Thomas G. W. Epperly Gary Kumfert Tamara Dahlgren Dietmar Ebner Jim Leek Adrian Prantl Scott Kohn Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore, California 94551 Abstract—High-performance scientific applications are challenges that must be overcome to successfully usually built from software modules written in multiple create large-scale applications. programming languages. This raises the issue of lan- Interoperability between languages involving in- guage interoperability which involves making calls be- compatible programming paradigms and type sys- tween languages, converting basic types, and bridging disparate programming models. Babel provides a feature- tems is inherently difficult. For example, dynamic rich, extensible, high-performance solution to the language memory management may be a feature of one interoperability problem currently supporting C, C++, language but left to the programmer in another. FORTRAN 77, Fortran 90/95, Fortran 2003/2008, Python, Errors may be reported explicitly versus via dynamic and Java. Babel supports object-oriented programming exceptions. Arrays may be represented in column- features and interface semantics with runtime-enforcement. versus row-major order and their indices start at 0 In addition to in-process language interoperability, Babel includes remote method invocation to support hybrid versus 1. These incompatibilities can make building, parallel and distributed computing -
Foreign Library Interface by Daniel Adler Dia Applications That Can Run on a Multitude of Plat- Forms
30 CONTRIBUTED RESEARCH ARTICLES Foreign Library Interface by Daniel Adler dia applications that can run on a multitude of plat- forms. Abstract We present an improved Foreign Function Interface (FFI) for R to call arbitary na- tive functions without the need for C wrapper Foreign function interfaces code. Further we discuss a dynamic linkage framework for binding standard C libraries to FFIs provide the backbone of a language to inter- R across platforms using a universal type infor- face with foreign code. Depending on the design of mation format. The package rdyncall comprises this service, it can largely unburden developers from the framework and an initial repository of cross- writing additional wrapper code. In this section, we platform bindings for standard libraries such as compare the built-in R FFI with that provided by (legacy and modern) OpenGL, the family of SDL rdyncall. We use a simple example that sketches the libraries and Expat. The package enables system- different work flow paths for making an R binding to level programming using the R language; sam- a function from a foreign C library. ple applications are given in the article. We out- line the underlying automation tool-chain that extracts cross-platform bindings from C headers, FFI of base R making the repository extendable and open for Suppose that we wish to invoke the C function sqrt library developers. of the Standard C Math library. The function is de- clared as follows in C: Introduction double sqrt(double x); We present an improved Foreign Function Interface The .C function from the base R FFI offers a call (FFI) for R that significantly reduces the amount of gate to C code with very strict conversion rules, and C wrapper code needed to interface with C. -
GWT W Akcji Zastosowania Bibliografia
Wprowadzenie AJAX Konfiguracja środowiska GWT w akcji Zastosowania Bibliografia GWT - Google Web Toolkit Anna Wrona, Janis Paraschidis, Igor Klimer Politechnika Wrocławska Informatyka 6 kwietnia 2009 Anna Wrona, Janis Paraschidis, Igor Klimer GWT - Google Web Toolkit Wprowadzenie AJAX Dlaczego GWT Konfiguracja środowiska Troszeczkę historii GWT w akcji Zalety i wady GWT Zastosowania Zawartość GWT Bibliografia Dlaczego GWT ? Duża popularność technologii AJAX Słaba kompatybilność przeglądarek (Internet Explorer, Safari, Mozilla Firefox, etc...) GWT nie jest kolejnym frameworkiem AJAXowym, będącym w praktyce zbiorem komponentów takich jak kalendarz czy kalkulator GWT jest kompilatorem skrośnym Javy do JavaScript’u, tak aby został on uruchomiony w przeglądarce Anna Wrona, Janis Paraschidis, Igor Klimer GWT - Google Web Toolkit Wprowadzenie AJAX Dlaczego GWT Konfiguracja środowiska Troszeczkę historii GWT w akcji Zalety i wady GWT Zastosowania Zawartość GWT Bibliografia Dlaczego GWT ? Duża popularność technologii AJAX Słaba kompatybilność przeglądarek (Internet Explorer, Safari, Mozilla Firefox, etc...) GWT nie jest kolejnym frameworkiem AJAXowym, będącym w praktyce zbiorem komponentów takich jak kalendarz czy kalkulator GWT jest kompilatorem skrośnym Javy do JavaScript’u, tak aby został on uruchomiony w przeglądarce Anna Wrona, Janis Paraschidis, Igor Klimer GWT - Google Web Toolkit Wprowadzenie AJAX Dlaczego GWT Konfiguracja środowiska Troszeczkę historii GWT w akcji Zalety i wady GWT Zastosowania Zawartość GWT Bibliografia Dlaczego GWT ? Duża popularność -
Building-Frontend-Pipeline Short
Building a Frontend Pipeline Nathaniel T. Schutta @ntschutta Ah JavaScript! It used to be so simple right? 1,500 line main.js. Our apps aren’t like that anymore though are they? JavaScript is a first class citizen now. Modern applications are many thousands of lines of JavaScript. We incorporate many libraries and frameworks. https://mobile.twitter.com/joeerl/status/930774515512201216 NPM all the things. JavaScript itself is evolving. Browsers are still an issue… The struggle is real. What do we do about it? Why do we need a pipeline at all? Not your older sister’s web apps. No longer a few thousands lines of JavaScript and jQuery. Adhoc approach can’t keep up with the complexity of modern JS apps. Apply the level of discipline to the frontend that we use on the backend. Linters to ensure our code doesn’t fall prey to common errors. Unit tests to ensure our changes didn’t break anything. Bundlers to minimize asynchronous requests to our servers. Transpilers so we can leverage ES6 in older browsers. Task runers to help tie it all together. JavaScript usage has exploded. Number one language on GitHub? Yep. Not a new phenomena either. We cannot afford to treat JavaScript as a one off. The same engineering discipline we use on “server side” code must apply. Of course for many of us, JavaScript *is* our server side language too! More than a few options. Try and clear some of that up today. Linters. Certain mistakes can be caught automatically. Static code analysis. Find bad patterns. Check style adherence.