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The IPython Notebook — IPython

The IPython Notebook is an interactive computational environment, in which you can combine code execution, rich text, mathematics, plots and rich media, as shown in this example session: It aims to be an agile tool for both exploratory computation and data analysis, and provides a platform to support reproducible research, since all inputs and outputs may be stored in a one-to-one way in notebook documents. There are two components: The IPython Notebook web application, for interactive authoring of literate computations, in which explanatory text, mathematics, computations and rich media output may be combined. Input and output are stored in persistent cells that may be edited in-place.Plain text documents, called notebooks, for recording and distributing the results of the rich computations. Features of the IPython Notebook web app Some of the main features of the IPython Notebook app include: Display rich data representations (e.g. Notebook documents

Related:  machine-learning-course

Machine Learning for Developers by Mike de Waard Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learning and terms as regression, unsupervised learning, Probability Density Function and many other definitions. If one switches to books there are books such as An Introduction to Statistical Learning with Applications in R and Machine Learning for Hackers who use programming language R for their examples. However R is not really a programming language in which one writes programs for everyday use such as is done with for example Java, C#, Scala etc. This is why in this blog machine learning will be introduced using Smile, a machine learning library that can be used both in Java and Scala.

Tutorial on Bayesian Networks with Netica 1. What is a Bayes net? A Bayes net is a model. It reflects the states of some part of a world that is being modeled and it describes how those states are related by probabilities. The model might be of your house, or your car, your body, your community, an ecosystem, a stock-market, etc. OpenTechSchool – Introducing IPython Notebook Until now we've worked with Python either directly via the interactive Python console, or by writing Python programs using a text editor. However, there are other ways to work with Python. IPython is a set of tools originally developed to make it easier for scientists to work with Python and data.

First impressions of the IPython Notebook July 2013 I've been using the IPython Notebook for less than a week, and I can already tell that there's no way I'm going back to my former data analysis workflow. Here are my first impressions. My former workflow Before discovering the IPython Notebook, I analyzed data with Python for many years using the following workflow. I first create a new directory for each experiment and then enter the following loop: InfiniBand As an interconnect, IB competes with Ethernet, Fibre Channel, and proprietary technologies[5] such as Cray's SeaStar. The technology is promoted by the InfiniBand Trade Association. Specification[edit] Performance[edit]

Machine Learning at Quora - Engineering at Quora - Quora Adapted from my original answer to How does Quora use machine learning in 2015? At Quora we have been using machine learning approaches for some time. We are constantly coming up with new approaches and making big improvements to the existing ones. It is important to note that all these improvements are first optimized and tested offline by using many different kinds of offline metrics but are always finally tested online through A/B tests. GeNIe and SMILE - Downloads We can compile SMILE for different platforms/specifications on request. Please email us for details. Distributions for Visual C++ contain three sets of libraries: two optimized builds for static and dynamic CRT, and another unoptimized build linking against debug DLL runtime without NDEBUG defined. smile.h and smilearn.h contain autolink #pragma directives and will select correct library, depending on CRT configuration of your project. DO NOT add smile.lib as additional linker input in project settings - smile.h takes care of that.

A gallery of interesting IPython Notebooks · ipython/ipython Wiki This page is a curated collection of IPython notebooks that are notable for some reason. Feel free to add new content here, but please try to only include links to notebooks that include interesting visual or technical content; this should not simply be a dump of a Google search on every ipynb file out there. Important contribution instructions: If you add new content, please ensure that for any notebook you link to, the link is to the rendered version using nbviewer, rather than the raw file. Simply paste the notebook URL in the nbviewer box and copy the resulting URL of the rendered version. This will make it much easier for visitors to be able to immediately access the new content.

Non-Personalized Recommender systems with Pandas and Python - Artificial Intelligence in Motion Hi all, At the last PythonBrasil I gave a tutorial about Python and Data Analysis focused on recommender systems, the main topic I've been studying for the last years. There is a popular python package among the statisticians and data scientists called Pandas. I watched several talks and keynotes about it, but I didn't have a try on it. The tutorial gave me this chance and after the tutorial me and the audience fell quite excited about the potential and power that this library gives.

Related:  Python