https://github.com/yining1023/bots-and-machine-learning

Syllabus for bots and machine learning at School of Machines, Making & Make-Believe
https://github.com/yining1023/bots-and-machine-learning

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Syllabus for bots and machine learning at School of Machines, Making & Make-Believe

• Host: GitHub
• URL: https://github.com/yining1023/bots-and-machine-learning
• Owner: yining1023
• Created: 2019-07-02T08:10:16.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-12-09T17:22:11.000Z (about 2 years ago)
• Last Synced: 2024-10-31T00:44:17.186Z (about 2 months ago)
• Language: JavaScript
• Size: 20.7 MB
• Stars: 7
• Watchers: 2
• Forks: 2
• Open Issues: 15
• Metadata Files:
  • Readme: README.md

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README

        
## Bots and Machine Learning

Syllabus for Bots and Machine Learning at The School of Machines, Making & Make Believe

## Get started

To run each examples, open your terminal, type in the following commands:

```

$ git clone https://github.com/yining1023/bots-and-machine-learning.git

$ cd bots-and-machine-learning

$ python -m SimpleHTTPServer     # $ python3 -m http.server (if you are using python 3)

```

Go to `localhost:8000` in your browser, you will see a directory list like this:

- bodypix/

- bodypix-parts/

- codeInClass/

- ImageClassification/

- KNNImageClassification/

- p5+arduino/

- p5+arduino+mobileNet/

- poseNet/

- README.md

- runway-attnGAN/

- runway-im2txt/

- teachableMachineImage/

- teachableMachineSound/

- twitterbot/

Click into each topic, you will see the example for each topic.

### 1. Twitter bot

Tweet text and image

[Code](./twitterbot/twitterbot_image)

### 2. Image Classifier

Presentation: [Slides](https://docs.google.com/presentation/d/1s0iT382Pl1DMGKb5xhk7_V3DlW1QQHfHs4snNoS_sIU/edit?usp=sharing)

- What’s Artificial Intelligence, Machine Learning, Deep learning?

- Supervised Learning, Unsupervised Learning, Reinforcement Learning

- Machine Learning output types: Regression, Classification, Clustering, Sequence prediction

- Existing Machine Learning use cases and creative projects

- Machine Learning tools / libraries: Tensorflow, Keras

- Introduction to ml5.js, tf.js, examples, experiments, datasets

Image Classifier with ml5.js

[Code](./ImageClassification)

### 3. Twiiter bot + MobileNet

Nodejs + tfjs-node: Twitter bot tweet the mobileNet result of an image

[Code](./twitterbot/twitterbot_mobileNet)

### 4. KNN Image Classifition

[Code](./KNNImageClassification)

- KNN Image Classifier Video

- KNN Image Classifier Video + Sound

- KNN Image Classifier Video + Square

### 5. Serial communication between arduino and p5.js

-  p5+arduino [Code](./p5+arduino)

-  p5+arduino+mobileNet [Code](./p5+arduino+mobileNet)

### 6. PoseNet, BodyPix

- PoseNet [Code](./posenet)

- BodyPix [Code](./bodypix)

- BodyPix with colorful body parts [Code](./bodypix-parts)

### 7. Teachable Machine

- Image classifier [Code](./teachableMachineImage)

- Sound classifier [Code](./teachableMachineSound)

- Poses classifier [Code](./teachableMachinePoses)

### 8. Runway

- im2txt [Code](./runway-im2txt)

- AttnGAN [Code](./runway-attnGAN)