Difference between revisions of "TensorFlow Playground"
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* [http://playground.tensorflow.org TensorFlow Playground | Daniel Smilkov] and [[Creatives#Shan Carter |Shan Carter]] | * [http://playground.tensorflow.org TensorFlow Playground | Daniel Smilkov] and [[Creatives#Shan Carter |Shan Carter]] | ||
| − | ** written in [[ | + | ** written in [[JavaScript]] (TypeScript) using [[JavaScript#D3.js|D3.js]] |
** [http://github.com/tensorflow/playground open source on GitHub] | ** [http://github.com/tensorflow/playground open source on GitHub] | ||
* [[TensorFlow]] | * [[TensorFlow]] | ||
Latest revision as of 23:06, 5 December 2023
YouTube search... ...Google search
- TensorFlow Playground | Daniel Smilkov and Shan Carter
- written in JavaScript (TypeScript) using D3.js
- open source on GitHub
- TensorFlow
- TensorBoard
- TensorBoard: Graph Visualization
- Visualization
- Colaboratory (Colab)
- TensorWatch
- ConvNetJS | Andrej Karpathy
- Deep Playground — How To Play With A Neural Network Right Here In Your Browser | Adarsh Verma - Fossbytes
Deep playground is an interactive visualization of neural networks. Tailor the playground to a specific topic or lesson. Just choose which features you’d like to be visible below (in the This Is Cool, Can I Repurpose It? section) then save this link, or refresh the page.
Why Neural Networks Can Learn Anything
Spiral Example
