Making it easier to discover datasets

Setembro 7th, 2018
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Novo recurso da google para identificar conjuntos de dados.

In today’s world, scientists in many disciplines and a growing number of journalists live and breathe data. There are many thousands of data repositories on the web, providing access to millions of datasets; and local and national governments around the world publish their data as well. To enable easy access to this data, we launched Dataset Search, so that scientists, data journalists, data geeks, or anyone else can find the data required for their work and their stories, or simply to satisfy their intellectual curiosity.

IFORS Developing Countries OR Resources Website

Julho 5th, 2018
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Artigos e software relacionado com Investigação Operacional

Click below on required topic headings to access papers or click here to access International Abstracts in OR

SNS Trabalhadores por Grupo Profissional

Junho 23rd, 2018

sem nome

Bons dados sobre o SNS

Apurar o nº de trabalhadores (empregos), por instituição e por grupo profissional, com contrato de trabalho ativo no mês de análise.

Número de trabalhadores (empregos) com contrato de trabalho ativo no mês em análise, por entidade e por mês, discriminado pelos grupos profissionais: Médicos (sem contabilizar Internos), Médicos Internos, Enfermeiros, Técnicos Superiores de Saúde, Técnicos Superiores de Diagnóstico e Terapêutica, Assistentes Técnicos, Assistentes Operacionais, Técnicos Superiores, Informáticos e Outros.

Nota: Os dados apresentados dizem respeito aos trabalhadores vinculados com contrato de trabalho às entidades do setor público administrativo (SPA) e entidades públicas empresarias (EPE) que se encontram sob a tutela do Ministério da Saúde, aos quais acrescem ainda os profissionais que exercem funções nos estabelecimentos hospitalares em regime de parceria público-privada integrados no Serviço Nacional de Saúde. (Ver anexo – Número de Profissionais nos Estabelecimentos Hospitalares em Regime de Parceira Público-Privada).

The 5 Computer Vision Techniques

Junho 12th, 2018
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Boa introdução ao tema da visão por computador

The 5 Computer Vision Techniques That Will Change How You See The World

Computer Vision is one of the hottest research fields within Deep Learning at the moment. It sits at the intersection of many academic subjects, such as Computer Science (Graphics, Algorithms, Theory, Systems, Architecture), Mathematics (Information Retrieval, Machine Learning), Engineering (Robotics, Speech, NLP, Image Processing), Physics (Optics), Biology (Neuroscience), and Psychology (Cognitive Science). As Computer Vision represents a relative understanding of visual environments and their contexts, many scientists believe the field paves the way towards Artificial General Intelligence due to its cross-domain mastery.

So what is Computer Vision?

Basketball Stat Cherry Picking

Maio 23rd, 2018
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Deep into the NBA playoffs, we are graced with stats-o-plenty before, during, and after every game. Some of the numbers are informative. Most of them are randomly used to illustrate a commentator’s point.

One of the most common stats is the conditional that says something like, “When player X scores at least Y points, the team wins 90 percent of their games.” It implies a cause-and-effect relationship.

The Cleveland Cavaliers won the most games when LeBron James scored 30 or more points. So James should just score that many points every time. Easy. I should be a coach.

It’s a bit of stat cherry picking, trying to find something in common among games won. So to make things easier, and for you to wow your friends during the games, I compiled winning percentages for several stats during the 2017-18 regular season. Select among the star players still in the playoffs.

50 Great Examples of Data Visualization

Abril 30th, 2018

clique na imagem para seguir o linkBons exemplos de representações gráficas

Wrapping your brain around data online can be challenging, especially when dealing with huge volumes of information.

And trying to find related content can also be difficult, depending on what data you’re looking for.

But data visualizations can make all of that much easier, allowing you to see the concepts that you’re learning about in a more interesting, and often more useful manner.

Below are 50 of the best data visualizations and tools for creating your own visualizations out there, covering everything from Digg activity to network connectivity to what’s currently happening on Twitter.

SQL Server Data Mining News

Março 5th, 2018
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Um site com visão da microsoft para o data mining

Welcome to

This site has been designed by the SQL Server Data Mining team to provide the SQL Server community with access to and information about our in-database data mining and analytics features.  SQL Server 2000 was the first major database release to put analytics in the database.  Catch up with the latest SQL Server Data Mining news in our newsletter.

SQL Server 2012 SP1 Data Mining Add-ins for Office (with 32-bit or 64-bit Support)

The Data Mining Add-ins allow you to harness the power of SQL Server 2012 predictive analytics in Excel and Visio and they have been updated to include 32-bit or 64-bit support for Office 2010 or Office 2013. Use Table Analysis Tools to get insight with a couple of clicks. Use the Data Mining tab for full-lifecycle data mining, and build models which can be exported to a production server.  Visualize your models in Visio.

SQL Server 2012 Data Mining

Microsoft expert Rafal Lukawiecki provides free and paid videos on data mining for SQL Server 2012 at Project Botticelli. The website has other Microsoft BI topics too from leading Microsoft experts.

SQL Server DM with Excel 2010 and PowerPivot

Microsoft MVP Mark Tabladillo shows you how to unleash SQL Server 2008 Data Mining with Excel 2010 and SQL Server PowerPivot for Excel, Microsoft’s new self-service BI offering.

When Variable Reduction Doesn’t Work

Janeiro 31st, 2018
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Um bom exemplo de como os procedimentos habituais nem sempre funcionam

Summary: Exceptions sometimes make the best rules.  Here’s an example of well accepted variable reduction techniques resulting in an inferior model and a case for dramatically expanding the number of variables we start with.

of the things that keeps us data scientists on our toes is that the well-established rules-of-thumb don’t always work.  Certainly one of the most well-worn of these rules is the parsimonious model; always seek to create the best model with the fewest variables.  And woe to you who violate this rule.  Your model will over fit, include false random correlations, or at very least will just be judged to be slow and clunky.

Certainly this is a rule I embrace when building models so I was surprised and then delighted to find a well conducted study by Lexis/Nexis that lays out a case where this clearly isn’t true.

How signal processing can be used to identify patterns in complex time series

Janeiro 31st, 2018
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Uso de técnicas de processamento de sinal em séries cronológicas

The trend and seasonality can be accounted for in a linear model by including sinusoidal components with a given frequency. However, finding the appropriate frequency for each sinusoidal component requires a little more digging. This post shows how to use fast Fourier transforms to find these frequencies.

How To Forecast Time Series Data With Multiple Seasonal Periods

Janeiro 31st, 2018
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Análise de séries complexas com múltiplos períodos sazonais

Time series data is produced in domains such as IT operations, manufacturing, and telecommunications. Examples of time series data include the number of client logins to a website on a daily basis, cell phone traffic collected per minute, and temperature variation in a region by the hour. Forecasting a time series signal ahead of time helps us make decisions such as planning capacity and estimating demand. Previous time series analysis blog posts focused on processing time series data that resides on Greenplum database using SQL functions. In this post, I will examine the modeling steps involved in forecasting a time series sequence with multiple seasonal periods. The various steps involved are outlined below:

  • Multiple seasonality is modelled with the help of fourier series with different periods
  • External regressors in the form of fourier terms are added to an ARIMA model to account for the seasonal behavior
  • Akaike Information Criteria (AIC) is used to find the best fit model