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Data Science - Ciencia de Datos - Ciência dos Dados
Translating the human rationality in numbers, using math and computing to solve real world problems
Curated by RodFiguerosky
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So you call yourself a data scientist?

So you call yourself a data scientist? | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Sponsored Post The trend for Big Data isn't showing any signs of slowing down. Here in Silicon Valley, we're amid a second California gold rush, but this time, we're turning nuggets of data, not go...
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Big Data 101: How Higher Ed Is Teaching Data Science

Big Data 101: How Higher Ed Is Teaching Data Science | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Universities are developing analytics curricula to educate future data professionals, with help from IBM and other partners.

Via Pierre Levy
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Datasets and Tasks - DATA-MINING-CUP by prudsys


Via Dr. Guido Möser
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Dr. Guido Möser's curator insight, October 11, 2013 11:59 AM

All Data-Mining Cup (powered by prudsys) datasets and tasks available.

 

This is a very helpful collection of datasets around different tasks (SPAM classification task, auction data, webshop transactions etc.).

 

 Thanks guys!

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CS 229: Machine Learning by Stanford University | Stanford / Computer Science

CS 229: Machine Learning by Stanford University | Stanford / Computer Science | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
This course (CS229) -- taught by Professor Andrew Ng -- provides a broad introduction to machine learning and statistica - Free Course
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Highcharts - Interactive JavaScript charts for your webpage

Highcharts - Interactive JavaScript charts for your webpage | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Highcharts - Interactive JavaScript charts for your web projects.

Via marianne
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Gephi, an open source graph visualization and manipulation software

Gephi, an open source graph visualization and manipulation software | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Gephi is an open-source software for visualizing and analyzing large networks graphs. Gephi uses a 3D render engine to display graphs in real-time and speed up the exploration.
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Tsunami - Media

RodFiguerosky's insight:

F# + Excel = Tsunami

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Overview — NetworkX

Overview — NetworkX | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
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Blog de Estadística: Máster Universitario en Minería de Datos e Inteligencia de Negocios

Blog de Estadística: Máster Universitario en Minería de Datos e Inteligencia de Negocios | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
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David McCandless: The beauty of data visualization | Video on TED.com

David McCandless turns complex data sets (like worldwide military spending, media buzz, Facebook status updates) into beautiful, simple diagrams that tease out unseen patterns and connections.
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MOOC - Waikato Courses - Data Mining with Weka (free) - Enrolment open!


Via Dr. Guido Möser
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Dr. Guido Möser's curator insight, September 5, 2013 10:30 AM

MOOC - The University of Waikato - Free online course: Data Mining with Weka

 

Course starts September 9, 2013 - Enrolment is open!

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Clustering Memes in Social Media


Via ukituki
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ukituki's curator insight, October 12, 2013 2:43 PM

The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different kinds of activities, for example engineered misinformation campaigns versus spontaneous communication. Such detection problems require a formal definition of meme, or unit of information that can spread from person to person through the social network. Once a meme is identified, supervised learning methods can be applied to classify different types of communication. The appropriate granularity of a meme, however, is hardly captured from existing entities such as tags and keywords. Here we present a framework for the novel task of detecting memes by clustering messages from large streams of social data. We evaluate various similarity measures that leverage content, metadata, network features, and their combinations. We also explore the idea of pre-clustering on the basis of existing entities. A systematic evaluation is carried out using a manually curated dataset as ground truth. Our analysis shows that pre-clustering and a combination of heterogeneous features yield the best trade-off between number of clusters and their quality, demonstrating that a simple combination based on pairwise maximization of similarity is as effective as a non-trivial optimization of parameters. Our approach is fully automatic, unsupervised, and scalable for real-time detection of memes in streaming data.

luiy's curator insight, October 14, 2013 11:25 AM

The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different kinds of activities, for example engineered misinformation campaigns versus spontaneous communication. Such detection problems require a formal definition of meme, or unit of information that can spread from person to person through the social network. Once a meme is identified, supervised learning methods can be applied to classify different types of communication. The appropriate granularity of a meme, however, is hardly captured from existing entities such as tags and keywords. Here we present a framework for the novel task of detecting memes by clustering messages from large streams of social data. We evaluate various similarity measures that leverage content, metadata, network features, and their combinations. We also explore the idea of pre-clustering on the basis of existing entities. A systematic evaluation is carried out using a manually curated dataset as ground truth. Our analysis shows that pre-clustering and a combination of heterogeneous features yield the best trade-off between number of clusters and their quality, demonstrating that a simple combination based on pairwise maximization of similarity is as effective as a non-trivial optimization of parameters. Our approach is fully automatic, unsupervised, and scalable for real-time detection of memes in streaming data.

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Interactive 3D in Shiny (shinyRGL) | Trestle Technology

Interactive 3D in Shiny (shinyRGL) | Trestle Technology | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
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Coursera

Coursera | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Take free online classes from 80+ top universities and organizations.
RodFiguerosky's insight:

Big Data in Education 24th oct

 

 

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Significant Scales in Community Structure

Significant Scales in Community Structure | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Many complex networks show signs of modular structure, uncovered by community detection. Although many methods succeed in revealing various partitions, it remains difficult to detect at what scale some partition is significant.

Via Claudia Mihai, ukituki
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Eric L Berlow's curator insight, October 17, 2013 11:48 AM

Evaluating the statistical significance of modules within networks identified by community detection algorithms

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Why We Hate Infographics (And Why You Should)

Why We Hate Infographics (And Why You Should) | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Infographic of infographics
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crossfilter.js | Becoming A Data Scientist

crossfilter.js | Becoming A Data Scientist | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Posts about crossfilter.js written by Eamonn O'Loughlin
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pajek [Pajek Wiki]

pajek [Pajek Wiki] | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
RodFiguerosky's insight:
Pajek - Program for Large Network Analysis
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SoNIA - Social Network Image Animator

SoNIA - Social Network Image Animator | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
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Creating Excel files with Python and XlsxWriter — XlsxWriter Documentation

Creating Excel files with Python and XlsxWriter — XlsxWriter Documentation | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
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Visualization of Anomalies in Dynamic Networks with NodeXL

Extension of NodeXL for visualizing large time-evolving networks and Significant Anomalous Regions in such networks (Visualization of Anomalies in Dynamic Networks with NodeXL (+playlist): http://t.co/IctBCzWYSj...

Via João Greno Brogueira, ukituki
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Best Blogs for Data Miners and Data Scientists

What are the best blogs for data miners and data scientists to read? I summarize the discussion on Quora and add my favorites.
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Information Is Beautiful | Rape: A Lack of Conviction

Information Is Beautiful | Rape: A Lack of Conviction | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it

Via marianne
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Researchers to Open-Source Model they say has Nailed Sentiment Analysis

Researchers to Open-Source Model they say has Nailed Sentiment Analysis | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
A group of researchers from Stanford has been working on deep learning models that can make sense of whole sentences at a time, and has recently trained its models on a large collection of online movie reviews.

Via Ed Stenson
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Entenda a Ciência dos Dados

Entenda a Ciência dos Dados | Data Science - Ciencia de Datos - Ciência dos Dados | Scoop.it
Transformar Dados em Informações Mensuráveis, para então usufruir em forma de Conhecimento é algo há muito explorado pelos sistemas de BI (Business Intelligence), mas com o aumento de fontes (Redes...
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University of Waikato Launches MOOC on Data Mining - HispanicBusiness.com

HAMILTON, New Zealand, Aug.
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