https://github.com/drujensen/diabetes
Crystal SHAINet example using Pima Indians dataset for Diabetes
https://github.com/drujensen/diabetes
artificial-intelligence crystal deep-learning machine-learning pima-diabetes-data shainet
Last synced: 5 months ago
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Crystal SHAINet example using Pima Indians dataset for Diabetes
- Host: GitHub
- URL: https://github.com/drujensen/diabetes
- Owner: drujensen
- License: mit
- Created: 2017-12-28T21:29:30.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2021-11-18T05:51:13.000Z (over 4 years ago)
- Last Synced: 2025-08-26T19:02:09.766Z (7 months ago)
- Topics: artificial-intelligence, crystal, deep-learning, machine-learning, pima-diabetes-data, shainet
- Language: Crystal
- Size: 28.3 KB
- Stars: 5
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Deep Learning Example using SHAInet
This workbook demonstrates how to create a Deep Learning network using [SHAInet](https://github.com/NeuraLegion/shainet). We will be using the [Pima Indians dataset](https://archive.ics.uci.edu/ml/datasets/Pima+Indians+Diabetes) to predict diabetes.
## Installation
This requires crystal 0.23.1
## Usage
This project uses crystal's playground. You can load and run the playground workbook using:
```bash
shards install
crystal play
open http://localhost:8080
```
Then select the Workbook -> Diabetes from the menu.
You can also compile and run the application:
```bash
crystal run src/diabetes.cr
```
## Contributing
1. Fork it ( https://github.com/drujensen/diabetes/fork )
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create a new Pull Request
## Contributors
- [drujensen](https://github.com/drujensen) Dru Jensen - creator, maintainer