Infographics

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Montes de infographics no pinterest. Podem servir como fonte de inspiração.

Infographics


Tita Maria

Tita Maria

Infographics

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NASA PCoE Datasets

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12 tabelas de dados q podem ser úteis
PCoE Datasets

Overview

The Prognostics Data Repository is a collection of data sets that have been donated by various universities, agencies, or companies. The data repository focuses exclusively on prognostic data sets, i.e., data sets that can be used for development of prognostic algorithms. Mostly these are time series of data from some nominal state to a failed state. The collection of data in this repository is an ongoing process.

Publications making use of databases obtained from this repository are requested to acknowledge both the assistance received by using this repository and the donators of the data. This will help others to obtain the same data sets and replicate your experiments. It also provides credit to the donators.

Users employ the data at their own risk. Neither NASA nor the donators of the data sets assume any liability for the use of the data or any system developed using the data.

If you have suggestions concerning the repository send email to kai.goebel [at] nasa.gov Thank you and please come again.

Datasets

[Algae Raceway Data Set] [CFRP Composites Data Set] [Milling Data Set ] [Bearing Data Set] [Battery Data Set] [Turbofan Engine Degradation Simulation Data Set] [PHM08 Challenge Data Set] [IGBT Accelerated Aging Sata Set] [Trebuchet Data Set] [FEMTO Bearing Data Set] [Randomized Battery Usage Data Set] [Capacitor Electrical Stress Data Set]

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Linking Open Data cloud diagram

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O maravilhoso mundo dos dados abertos e ligados

This web page is the home of the LOD cloud diagram. This image shows datasets that have been published in Linked Data format, by contributors to the Linking Open Data community project and other individuals and organisations. It is based on metadata collected and curated by contributors to the Data Hub as well as on metadata extracted from a crawl of the Linked Data web conducted in April 2014. Clicking the image will take you to an image map, where each dataset is a hyperlink to its homepage.

The diagram is maintained by Richard Cyganiak (Insight Centre for Data Analytics at NUI Galway) and Anja Jentzsch (HPI). For any questions and comments, please email richard@cyganiak.de and mail@anjajentzsch.de.

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Theoretical Motivations for Deep Learning

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Uma boa introdução ao Deep Learning uma nova técnica de machine learning.

This post is based on the lecture “Deep Learning: Theoretical Motivations” given by Dr. Yoshua Bengio at Deep Learning Summer School, Montreal 2015. I highly recommend the lecture for a deeper understanding of the topic.

Deep learning is a branch of machine learning algorithms based on learning multiple levels of representation. The multiple levels of representation corresponds to multiple levels of abstraction. This post explores the idea that if we can successfully learn multiple levels of representation then we can generalize well.

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R and the Nobel Prize API

Blog com vários tutoriais para usar estatísticas não paramétricas simples em R

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Um bom exemplo do que se pode fazer com o R e uma API q serviços de dados.

he Nobel Prizes. Love them? Hate them? Are they still relevant, meaningful? Go on admit it, you always imagined you would win one day.

Whatever you think of them, the 2015 results are in. What’s more, the good people of the Nobel Foundation offer us free access to data via an API. I’ve published a document over at RPubs, showing some of the ways to access and analyse their data using R. Just to get you started:

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KNIME Community Contributions

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Boa fonte de novos nós do KNIME, evitando q estejamos a programar algo q já foi programado antes.

KNIME Community Contributions offer a wide range of KNIME nodes from different application areas, such as chemo- and bioinformatics, image processing, or information retrieval. In contrast to the extensions available via the standard KNIME Update Site they are provided and maintained by various community developers.

The Trusted Community Contributions can easily be installed by selecting File -> Install KNIME Extensions in KNIME. Additional extensions are available by enabling the Update Site in KNIME via File -> Preferences -> Install/Update -> Available Update Sites. See the update site guide for details.

You can also download the whole update site as a ZIP archive and add the ZIP to the Available Update Sites (see above).

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norsecorp cyber attack info

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Um site dinâmico q mapeia informação sobre ciberataques em tempo real

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The Statistics Portal

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Um portal cheio de facts & figures
One of the world’s largest statistics portals

We pride ourselves in being one of the world’s first and only companies to bring together data from over 18,000 sources.
Our research analysts source the most up-to-date statistical data from around the globe; our analytical approach and efficient research processes enable us to supply our clients with the data that is relevant to them.

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Ternary Diagrams Using R

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Exemplo de criação de diagramas ternários no R

Ternary Diagrams Using R:  An Example Using Election Outcomes

A tutorial by D. M. Wiig

In part one of this tutorial I discussed creating a ternary diagram using a simple data frame that contained five hypothetical cases. In this tutorial I will expand on that foundation by creating a more informative ternary diagram using live data.

A useful application of this package in social science research is creating a visual display of parliamentary election outcomes. Specifically we can use a ternary graph to examine the distribution of seats in the British House of Commons over a period of time. Since the UK uses a proportional system to allocate seats in the House of Commons there can be a variety of outcomes in any given national election.

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Science Isn’t Broken

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Um bom blog com discussões interessantes e ilustrações muito boas

The Scientific Method 7:00 AM Aug 19, 2015

Science Isn’t Broken

It’s just a hell of a lot harder than we give it credit for.

By

Graphics by Ritchie King

If you follow the headlines, your confidence in science may have taken a hit lately.

Peer review? More like self-review. An investigation in November uncovered a scam in which researchers were rubber-stamping their own work, circumventing peer review at five high-profile publishers.

Hack Your Way To Scientific Glory

You’re a social scientist with a hunch: The U.S. economy is affected by whether Republicans or Democrats are in office. Try to show that a connection exists, using real data going back to 1948. For your results to be publishable in an academic journal, you’ll need to prove that they are “statistically significant” by achieving a low enough p-value.
“Science is great, but it’s low-yield. Most experiments fail. That doesn’t mean the challenge isn’t worth it, but we can’t expect every dollar to turn a positive result. Most of the things you try don’t work out — that’s just the nature of the process.”

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