https://github.com/shiffman/tensorflow-js-examples
Working on some new examples with tensorflow.js and p5.js
https://github.com/shiffman/tensorflow-js-examples
javascript machine-learning ml5 p5js tensorflow tensorflow-js
Last synced: 3 months ago
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Working on some new examples with tensorflow.js and p5.js
- Host: GitHub
- URL: https://github.com/shiffman/tensorflow-js-examples
- Owner: shiffman
- Created: 2018-04-25T20:14:49.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-09-22T18:57:50.000Z (over 5 years ago)
- Last Synced: 2025-03-10T21:53:14.828Z (3 months ago)
- Topics: javascript, machine-learning, ml5, p5js, tensorflow, tensorflow-js
- Language: JavaScript
- Homepage:
- Size: 833 KB
- Stars: 168
- Watchers: 11
- Forks: 31
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
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README
# TensorFlow.js Examples
## XOR vanilla neural network
## Doodle Classifier
This repo is experimental and in progress. It is an "MNIST"-style classification example using the [Google QuickDraw dataset](https://quickdraw.withgoogle.com/data), [p5js](https://p5js.org/), and [tensorflow.js](https://js.tensorflow.org). It is loosely based on the [tfjs MNIST example](https://github.com/tensorflow/tfjs-examples/tree/master/mnist).
### Reference
* [JS Doodle Classifier video tutorials](https://www.youtube.com/watch?v=pqY_Tn2SIVA&list=PLRqwX-V7Uu6Zs14zKVuTuit6jApJgoYZQ)
* [ml4a ofx Doodle Classifier](https://ml4a.github.io/guides/DoodleClassifier/)
### RoadMap
* [ ] Simplify model removing convolutional layers. The idea is for this to be a dropdead simple example that I can use to explain tensorflow.js and the layers API. I'd like to cover convolutional neural networks as a secondary example.
* [ ] Incorporate testing data. At the moment [no any validation / testing data](https://github.com/shiffman/Tensorflow-JS-Doodle-Classifier/blob/master/classifier.js#L53) is included during training. For clarity of the example I might like to run the testing as a separate function. What do the results mean me if I give it `null` data?
* [ ] Guess user drawings in real-time.
* [ ] Train with a much larger dataset.
* [ ] Save model using local storage or to JSON file.
* [ ] Bring the idea of a higher level `Classifier` class that wraps keras layers into [ml5](https://ml5js.github.io/).
### Neuro-Evolution
* [Flappy Bird Demo: Learning](https://shiffman.github.io/Tensorflow-JS-Examples/04_neuro_evolution_flappy/)
* [Flappy Bird Demo: Loading Saved Model](https://shiffman.github.io/Tensorflow-JS-Examples/04_neuro_load_flappy/)
* [Steering Ecosystem Simulation Demo](https://shiffman.github.io/Tensorflow-JS-Examples/05_neuro_evolution_steering/)