Allocated time to media per person
#statistics #visualization
Source:Nielsen
----------
@machinelearning_tuts
#statistics #visualization
Source:Nielsen
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@machinelearning_tuts
Tinker With a Neural Network Right Here in Your Browser
This was created by Daniel Smilkov and Shan Carter. This is a continuation of many peopleβs previous work β most notably Andrej Karpathyβs #convnet.js demo and Chris Olahβs articles about neural networks.
Via: @cedeeplearning
https://playground.tensorflow.org/
#visualization #neural_networks
This was created by Daniel Smilkov and Shan Carter. This is a continuation of many peopleβs previous work β most notably Andrej Karpathyβs #convnet.js demo and Chris Olahβs articles about neural networks.
Via: @cedeeplearning
https://playground.tensorflow.org/
#visualization #neural_networks
playground.tensorflow.org
Tensorflow β Neural Network Playground
Tinker with a real neural network right here in your browser.
π»COVID-19 Visualized: The power of effective visualizations for pandemic storytelling
Clear, succinct data visualizations can be powerful tools for telling stories and explaining phenomena. This article demonstrates this concept as relates to the COVID-19 pandemic.
π‘By Matthew Mayo, KDnuggets.
ββββββββββββββββ
link: https://www.kdnuggets.com/2020/03/covid-19-visualized.html
πVia: @cedeeplearning
#visualization
#covid19
#neuralnetworks
#deeplearning
Clear, succinct data visualizations can be powerful tools for telling stories and explaining phenomena. This article demonstrates this concept as relates to the COVID-19 pandemic.
π‘By Matthew Mayo, KDnuggets.
ββββββββββββββββ
link: https://www.kdnuggets.com/2020/03/covid-19-visualized.html
πVia: @cedeeplearning
#visualization
#covid19
#neuralnetworks
#deeplearning
π»Some points to visualizing your data
πVia: @cedeeplearning
πOther social media: https://linktr.ee/cedeeplearning
link: https://policyviz.com/2018/08/07/dataviz-cheatsheet/
#visualization
#bigdata
#machinelearning
#datascience
πVia: @cedeeplearning
πOther social media: https://linktr.ee/cedeeplearning
link: https://policyviz.com/2018/08/07/dataviz-cheatsheet/
#visualization
#bigdata
#machinelearning
#datascience
πΉTop 10 Data Visualization Tools for Every Data Scientist
At present, the data scientist is one of the most sought after professions. Thatβs one of the main reasons why we decided to cover the latest data visualization tools that every data scientist can use to make their work more effective.
1. Tableau
2. D3
3. Qlikview
4. Microsoft Power BI
5. Datawrapper
6. E Charts
7. Plotly
8. Sisense
9. FusionCharts
10. HighCharts
ββββββββββ
πVia: @cedeeplearning
πOther social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2020/05/top-10-data-visualization-tools-every-data-scientist.html
#datascience #visualization #datatools
#machinelearning #tableau #powerbi
At present, the data scientist is one of the most sought after professions. Thatβs one of the main reasons why we decided to cover the latest data visualization tools that every data scientist can use to make their work more effective.
1. Tableau
2. D3
3. Qlikview
4. Microsoft Power BI
5. Datawrapper
6. E Charts
7. Plotly
8. Sisense
9. FusionCharts
10. HighCharts
ββββββββββ
πVia: @cedeeplearning
πOther social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2020/05/top-10-data-visualization-tools-every-data-scientist.html
#datascience #visualization #datatools
#machinelearning #tableau #powerbi
βͺοΈ Visualizing the world beyond the frame
πΉResearchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.
πΉTo give computer vision models a fuller, more imaginative view of the world, researchers have tried feeding them more varied images. Some have tried shooting objects from odd angles, and in unusual positions, to better convey their real-world complexity. Others have asked the models to generate pictures of their own, using a form of artificial intelligence called GANs, or generative adversarial networks. In both cases, the aim is to fill in the gaps of image datasets to better reflect the three-dimensional world and make face- and object-recognition models less biased.
ββββββ
πVia: @cedeeplearning
πOther social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2020/visualizing-the-world-beyond-the-frame-0506
#deeplearning #GANs #math
#machinelearning #visualization
#AI #MIT #datascience
πΉResearchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.
πΉTo give computer vision models a fuller, more imaginative view of the world, researchers have tried feeding them more varied images. Some have tried shooting objects from odd angles, and in unusual positions, to better convey their real-world complexity. Others have asked the models to generate pictures of their own, using a form of artificial intelligence called GANs, or generative adversarial networks. In both cases, the aim is to fill in the gaps of image datasets to better reflect the three-dimensional world and make face- and object-recognition models less biased.
ββββββ
πVia: @cedeeplearning
πOther social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2020/visualizing-the-world-beyond-the-frame-0506
#deeplearning #GANs #math
#machinelearning #visualization
#AI #MIT #datascience