Difference between revisions of "Graphical Tools for Modeling AI Components"
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These range from a new interface for a tool that completely automates the process of creating models, to a new no-code visual interface for building, training and deploying models, all the way to hosted Jupyter-style notebooks for advanced users. Tools that allow visual drag-and-drop interface to streamline and simplify your process | These range from a new interface for a tool that completely automates the process of creating models, to a new no-code visual interface for building, training and deploying models, all the way to hosted Jupyter-style notebooks for advanced users. Tools that allow visual drag-and-drop interface to streamline and simplify your process | ||
| + | * [[TensorFlow]] | ||
| + | ** Playground | ||
| + | ** TensorBoard | ||
| + | * Nvidia Digits | ||
| + | * Knime | ||
* [http://perceptilabs.readme.io/docs PerceptiLabs] | * [http://perceptilabs.readme.io/docs PerceptiLabs] | ||
* [http://lobe.ai/ lobe] | * [http://lobe.ai/ lobe] | ||
* [http://www.cognitivescale.com/ CognitiveScale] - [https://www.cognitivescale.com/cortex/ Cortex Studio] | * [http://www.cognitivescale.com/ CognitiveScale] - [https://www.cognitivescale.com/cortex/ Cortex Studio] | ||
| + | * RapidMiner | ||
| + | * Orange | ||
| + | * Dataiku | ||
| + | * Dianne | ||
* [[H2O]] - [http://www.h2o.ai/products/h2o-driverless-ai/ Driverless AI] | * [[H2O]] - [http://www.h2o.ai/products/h2o-driverless-ai/ Driverless AI] | ||
* [[Microsoft]] [http://azure.microsoft.com/en-us/services/machine-learning/ Azure] - [http://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-create-portal-experiments Azure Machine Learning studio] | * [[Microsoft]] [http://azure.microsoft.com/en-us/services/machine-learning/ Azure] - [http://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-create-portal-experiments Azure Machine Learning studio] | ||
Revision as of 13:03, 7 December 2019
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- Development
- Model Zoo
- 10 Tools for Modeling AI Components – Machine Learning without the code | Jordi Cabot - Modeling Languages
These range from a new interface for a tool that completely automates the process of creating models, to a new no-code visual interface for building, training and deploying models, all the way to hosted Jupyter-style notebooks for advanced users. Tools that allow visual drag-and-drop interface to streamline and simplify your process
- TensorFlow
- Playground
- TensorBoard
- Nvidia Digits
- Knime
- PerceptiLabs
- lobe
- CognitiveScale - Cortex Studio
- RapidMiner
- Orange
- Dataiku
- Dianne
- H2O - Driverless AI
- Microsoft Azure - Azure Machine Learning studio
- IBM - Watson Studio SPSS Modeler
