The Beautiful Hidden Logic of Cities
Posted by Armando Brito Mendes | Filed under mapas SIG's, materiais ensino, materiais para profissionais, visualização
clicar na imagem para seguir o link
Padrões identificados em mapas de cidades.
After finishing my map of the most common road suffixes by length, I realized I could also map each individual road, colored by its suffix. This has led to the loveliest maps I’ve made.
Driving around your city, you’re probably somewhat aware of Avenues and Boulevards and Streets and Roads and so on. Here in Portland, at least, I know that Avenues run north-south and Streets run east-west. However, it’s hard to get an overall view of how all these road designations knit together. By coloring them, we can suddenly see a new, stunning view of what we normally take for granted.
Tags: captura de conhecimento, image mining, mapas
The Sleep Blanket
Posted by Armando Brito Mendes | Filed under visualização
clicar na imagem para seguir o link
A visualization of my son’s sleep pattern from birth to his first birthday. Crochet border surrounding a double knit body. Each row represents a single day. Each stitch represents 6 minutes of time spent awake or asleep #knitting #crochet #datavisualization
Tags: belo
Map of Best Breweries in America
Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, visualização
clicar na imagem para seguir o link
Um mapa com as melhores produtoras de cerveja artesanal nos EUA e uma rota otimizada com algoritmos genéticos
RateBeer puts out a list every year for top 100 breweries in the world. The rankings are based on reviews, range across styles, and historical performance (and maybe a bit of subjectivity). RateBeer just published the list for 2018. Here’s a map of the 73 U.S.-based breweries.
Brewery Road Trip, Optimized With Genetic Algorithm
Now that we know where they are, let’s find out how to visit all of them in one go.
Tags: belo, grafos, mapas, otimização, R-software, SIG
The list of 2018 visualization lists
Posted by Armando Brito Mendes | Filed under visualização
clique na imagem para seguir o link
Boa e longa lista de todo o tipo de visualizações.
The list of 2018 visualization lists
December 31, 2018
Officially a yearly habit now: the the list of visualization lists. So here is my list of visualisations, charts, graphics, maps, satellite journalism and science photography lists, version 2018.
Stories, Charts and Maps
@FlowingData: Best Data Visualization Projects of 2018
@ReutersGraphics: The Reuters graphics department takes a lookback at a year’s worth of work
@FiveThirtyEight: The 45 Best — And Weirdest — Charts We Made In 2018
@GuardianVisuals: 18 for 2018: a thread of our biggest projects of the year
@SCMPGraphics: 2018 in visuals: South China Morning Post’s infographic highlights
@qz: The best data visualization in 2018, according to data visualization experts
@HackAStory: The 40 best digital stories of 2018 listed for you by Hackastory
@EconDailyCharts: The 2018 Daily Chart advent calendar
@visualisingdata: 6 monthly reviews of the best of data visualisation @ftdata: Charts of the Year 2018: our writers’ picks @WSJGraphics: The Year in Graphics 2018
….
Tags: belo
Basketball Stat Cherry Picking
Posted by Armando Brito Mendes | Filed under estatística, visualização
clicar na imagem para seguir o link
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.
Tags: análise de dados
50 Great Examples of Data Visualization
Posted by Armando Brito Mendes | Filed under visualização
Bons 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.
Tags: belo, captura de conhecimento
imagens criadas por campos vetoriais
Posted by Armando Brito Mendes | Filed under materiais ensino, software, visualização
This website allows you to explore vector fields in real time.
“Vector field” is just a fancy way of saying that each point on a screen has some vector associated with it. This vector could mean anything, but for our purposes we consider it to be a velocity vector.
Now that we have velocity vectors at every single point, let’s drop thousands of small particles and see how they move. Resulting visualization could be used by scientist to study vector fields, or by artist to get inspiration!
Learn more about this project on GitHub
Stay tuned for updates on Twitter.
With passion,
Anvaka
Tags: belo
Pianogram
Posted by Armando Brito Mendes | Filed under estatística, visualização
clicar na imagem para seguir o link
Uma visualização em gráfico de barras das notas de canções
Pianogram
This is what you get when you cross a histogram and piano keys to show note distribution of songs. It’s the pianogram. View examples such as Fur Elise or the classic Chopsticks, or punch in your own MIDI-formatted song for a taste of the distribution ivories.
Here’s the distribution for Kenny Loggins’ Danger Zone.
Because why not.
Tags: belo
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
Tinker With a Neural Network
Posted by Armando Brito Mendes | Filed under software, visualização
clique na imagem para seguir o link
Uma excelente aplicação web para perceber como as redes neuronais funcionam
Um, What Is a Neural Network?
It’s a technique for building a computer program that learns from data. It is based very loosely on how we think the human brain works. First, a collection of software “neurons” are created and connected together, allowing them to send messages to each other. Next, the network is asked to solve a problem, which it attempts to do over and over, each time strengthening the connections that lead to success and diminishing those that lead to failure. For a more detailed introduction to neural networks, Michael Nielsen’s Neural Networks and Deep Learning is a good place to start. For a more technical overview, try Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
This Is Cool, Can I Repurpose It?
Please do! We’ve open sourced it on GitHub with the hope that it can make neural networks a little more accessible and easier to learn. You’re free to use it in any way that follows our Apache License. And if you have any suggestions for additions or changes, please let us know.
We’ve also provided some controls below to enable you tailor the playground to a specific topic or lesson. Just choose which features you’d like to be visible below then save this link, or refresh the page.
What Do All the Colors Mean?
Orange and blue are used throughout the visualization in slightly different ways, but in general orange shows negative values while blue shows positive values.
The data points (represented by small circles) are initially colored orange or blue, which correspond to positive one and negative one.
In the hidden layers, the lines are colored by the weights of the connections between neurons. Blue shows a positive weight, which means the network is using that output of the neuron as given. An orange line shows that the network is assiging a negative weight.
In the output layer, the dots are colored orange or blue depending on their original values. The background color shows what the network is predicting for a particular area. The intensity of the color shows how confident that prediction is.
What Library Are You Using?
We wrote a tiny neural network library that meets the demands of this educational visualization. For real-world applications, consider the TensorFlow library.
Credits
This was created by Daniel Smilkov and Shan Carter. This is a continuation of many people’s previous work — most notably Andrej Karpathy’s convnet.js demo and Chris Olah’s articles about neural networks. Many thanks also to D. Sculley for help with the original idea and to Fernanda Viégas and Martin Wattenberg and the rest of the Big Picture and Google Brain teams for feedback and guidance.
Tags: data mining, machine learning, web apps
