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The name of the service has changed Thank you for your patronage with PaintsChainer. Three years after its launch, we decided to change the name of the service to "Petalica Paint". We like to think of the creations blooming on this service as multicolored, like the petals of a flower, hence the new name's motif.

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키:167.1 몸무게:60.5

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훈련

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테스트

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데이터를 수집해요. 예)

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데이터를 수집해요. 예)

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키:167 발사이즈: 240

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Which Face Is Real has been developed by Jevin West and Carl Bergstrom at the University of Washington as part of the Calling Bullshit project. All images are either computer-generated from thispersondoesnotexist.com using the StyleGAN software, or real photographs from the FFHQ dataset of Creative Commons and public domain images.

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Fast drawing for everyone. AutoDraw pairs machine learning with drawings from talented artists to help you draw stuff fast.

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Can a neural network learn to recognize doodles? See how well it does with your drawings and help teach it, just by playing.

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아키네이터는 여러분의 마음을 읽을 수 있어, 여러분들이 생각한 인물을 마법처럼 맞출 수 있습니다. 실존 또는 가상의 인물을 머릿속에 떠오른 후 질문에 대답하세요. 그러면 아키네이터가 누구인지 맞출 것 입니다. 마법의 지니에게 도전해 보시겠습니까?

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Classification of plastic bottles and aluminum cans image data.

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Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections.

Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight!

When teaching data mining, we like to illustrate rather than only explain. And Orange is great at that. Used at schools, universities and in professional training courses across the world, Orange supports hands-on training and visual illustrations of concepts from data science. There are even widgets that were especially designed for teaching.

Add-ons Extend Functionality

Use various add-ons available within Orange to mine data from external data sources, perform natural language processing and text mining, conduct network analysis, infer frequent itemset and do association rules mining. Additionally, bioinformaticians and molecular biologists can use Orange to rank genes by their differential expression and perform enrichment analysis.

Ferenc Borondics, Ph.D.
Principal beamline scientist at SMIS
SOLEIL synchrotron, France

"The scientific community is in need of tools that allow easy construction of workflows and visualizations and are capable of analyzing large amounts of data. Orange is a powerful platform to perform data analysis and visualization, see data flow and become more productive. It provides a clean, open source platform and the possibility to add further functionality for all fields of science."

Francesca Vitali, Ph.D.
Research Assistant Professor
Center for Biomedical Informatics & Biostatistics, The University of Arizona

"I teach Orange workshops monthly to a diverse audience, from undergrad students to expert researchers. Orange is very intuitive, and, by the end of the workshop, the participants are able to perform complex data visualization and basic machine learning analyses. Most of our attendees have been able to incorporate this tool in their research practice."

Gad Shaulsky, Ph.D.
Molecular biologist and Director of Graduate Studies
Baylor College of Medicine, Houston, USA

"My laboratory produces large amounts of data from RNA-seq, ChIP-seq and genome resequencing experiments. Orange allows me to analyze my data even though I don't know how to program. It also allows me to communicate with my collaborators, who are experts in data mining, and with my colleagues and trainees."

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Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations.

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어제 우리는 뭘 배웠지?

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어제 우리는 뭘 배웠지?

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Join a game of kahoot here. Kahoot! is a free game-based learning platform that makes it fun to learn – any subject, in any language, on any device, for all ages!