GISTEMP Climate Spiral
Posted by Armando Brito Mendes | Filed under videos, visualização
Uma excelente visualização do aquecimento terrestre, veja até ao fim para uma evidência bastante clara
The visualization presents monthly global temperature anomalies between the years 1880-2021. These temperatures are based on the GISS Surface Temperature Analysis (GISTEMP v4), an estimate of global surface temperature change. Anomalies are defined relative to a base period of 1951-1980. The data file used to create this visualization can be accessed here.
The Goddard Institute of Space Studies (GISS) is a NASA laboratory managed by the Earth Sciences Division of the agency’s Goddard Space Flight Center in Greenbelt, Maryland. The laboratory is affiliated with Columbia University’s Earth Institute and School of Engineering and Applied Science in New York.
The ‘climate spiral’ is a visualization designed by climate scientist Ed Hawkins from the National Centre for Atmospheric Science, University of Reading. Climate spiral visualizations have been widely distributed, a version was even part of the opening ceremony of the Rio de Janeiro Olympics.
Tags: aquecimento da terra, belo, linhas circular, nasa
Noah Kalina’s averaged face over 7,777 days
Posted by Armando Brito Mendes | Filed under Data Science, videos
um vídeo obtido de 7 777 fotos em dias seguidos, com sobreposição usando machine learning (não é o gif da imagem)
Noah Kalina has been taking a picture of himself every day since January 11, 2000. He posted time-lapse videos in 2007, 2012, and 2020. Last year was the 20th of the project.
Usually Kalina’s videos are a straight up time-lapse using every photo. But in this collaboration with Michael Notter, 7,777 Days shows a smoother passage of time. Notter used machine learning to align the face pictures, and then each frame shows a 60-day average, which focuses on an aging face instead of everything else in the background. Tags:average, face, machine learning, Michael Notter, Noah Kalina
Voronoi diagram from smooshing paint between glass
Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, matemática, videos
clicar na imagem para seguir o link
Uma abordagem original aos diagramas de Voronoi.
Tags: belo, otimização
curso de KNIME
Posted by Armando Brito Mendes | Filed under mapas SIG's, materiais para profissionais, software, videos, visualização
clicar na imagem para seguir o link
Muito bom curso de KNIME, é introdutório mas introduz um grande número de funcionalidades.
KNIME Online Self-Training
Welcome to the KNIME Self-training course. The focus of this document is to get you started with KNIME as quickly as possible and guide you through essential steps of advanced analytics with KNIME. Optional and very useful topics such as reporting, KNIME Server and database handling are also included to give you an idea of what else is possible with KNIME.
- Installing KNIME Analytics Platform and Extensions
- Data Import / Export and Database / Big Data
- ETL
- Visualization
- Advanced Analytics
- Reporting
- KNIME Server
Tags: análise de dados, big data, data mining, Knime, text mining
SAP video analytics
Posted by Armando Brito Mendes | Filed under materiais para profissionais, videos
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SME Solutions and Partner Innovation
Tags: análise de dados, data mining
Hackers Remotely Kill a Jeep on the Highway
Posted by Armando Brito Mendes | Filed under videos
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Um exemplo dos problemas de segunrança ainda existentes no IoT.
Two hackers have developed a tool that can hijack a Jeep over the internet. WIRED senior writer Andy Greenberg takes the SUV for a spin on the highway while the hackers attack it from miles away.
Guardar
Tags: big data, data mining
Best Data Science Learning podcasts
Posted by Armando Brito Mendes | Filed under lições, materiais ensino, materiais para profissionais, videos
Muito bons podcasts tem temas introdutórios
We present the top 12 Data Science & Machine Learning related Podcasts by popularity on iTunes. Check out latest episodes to stay up-to-date & become a part of the data conversations!
By Bhavya Geethika Peddibhotla.
Learn Data science the new way by listening to these compelling story tellers, interviewers, educators and experts in the field. Data suggests that podcasting about Data Science is only growing!
Tags: análise de dados, big data, data mining, desnvolvimento de software, Estat Descritiva, machine learning
Straightforward Statistics Videos
Posted by Armando Brito Mendes | Filed under estatística, lições, materiais ensino, videos
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Montes de vídeos sobre todos os temas abordados em P&E
Video and Multimedia
Click on the following links. Please note these will open in a new window.
Descriptive Versus Inferential Statistics
https://www.youtube.com/watch?v=edEXEyvG4Wk
Illustrates the differential purposes served by descriptive and inferential techniques in conducting statistical analyses.
https://www.youtube.com/watch?v=L6hy1CY-OW4
Practical examples of descriptive and inferential statistics
https://www.youtube.com/watch?v=be9e-Q-jC-0
Simple Random Sampling, Convenience Sampling, Systematic Sampling, Cluster Sampling, Stratified Sampling
Types of Variables
https://www.youtube.com/watch?v=hZxnzfnt5v8
Describes the concepts of; a) unit of observation and b) variables and consequently the differences amongst the three major levels of measurement of variables, nominal, ordinal and interval/ratio.
Tags: análise de dados, Estat Descritiva
KNIME Image Processing (trusted extension)
Posted by Armando Brito Mendes | Filed under videos, visualização
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Apenas um exemplo das fantásticas possibilidades do KNIME
KNIME Image Processing (trusted extension)
Fri, 12/03/2010 – 13:09 — knime_admin
Overview
The KNIME Image Processing Plugin allows you to read in more than 120 different kinds of images (thanks to the Bio-Formats API) and to apply well known methods on images, like preprocessing. segmentation, feature extraction, tracking and classification in KNIME. In general these nodes operate on multi-dimensional image data (e.g. videos, 3D images, multi-channel images or even a combination of them), which is made possible by the internally used ImgLib2-API.
Several nodes are available to calculate image features (e.g. zernike-, texture- or histogram features) for segmented images (e.g. a single cell). These feature vectors can then be used to apply machine learning methods in order to train and apply a classifier.
Currently the Image Processing Plugin for KNIME provides ca. 100 nodes for (pre)-processing, filtering, segmentation, feature extraction, various views (2D, 3D), etc. and integrations for various other image processing tools are available (see used and integrated libraries)
Future directions include a full, bidirectional integration of ImageJ2. Such an integration allow the users to use directly use/update ImageJ2 Plugins inside KNIME as well as recording and running KNIME Workflows in ImageJ2. Please see ImageJ2 Integration (BETA) for more information.
For the first steps please consider the KNIME Image Processing User Manual (incomplete draft!).
Important Links
- How to install KNIME Image Processing?
- Example Workflows and Tutorials
- KNIME Image Processing Forum
- KNIME Image Processing (Webinar on YouTube)
- KNIME FAQ
- KNIME Image Processing on GitHub
- KNIME Image Processing News
- Contact
Tags: data mining, image mining, Knime
What is Data Virtualization?
Posted by Armando Brito Mendes | Filed under videos
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Muito clara introdução ao tema da virtualização de dados.
What is Data Virtualization?
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Tags: big data, data mining, DW \ BI
