Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/cgarciae/clearml-demo
https://github.com/cgarciae/clearml-demo
Last synced: 10 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/cgarciae/clearml-demo
- Owner: cgarciae
- License: mit
- Created: 2022-01-24T22:21:03.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-01-26T12:10:20.000Z (almost 3 years ago)
- Last Synced: 2024-11-07T09:39:29.683Z (2 months ago)
- Language: Python
- Size: 62.5 KB
- Stars: 0
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ClearML Demo
A small demo of ClearML modelling the titanic dataset using scikit-learn and Keras.
## SetupTo begin install the project requirements:
**pip**
```bash
pip install -r requirements.txt
```**poetry**
```bash
poetry install
poetry shell
```### ClearML
To setup clearml, run the following command:```bash
clearml login
```If you are running a custom server manually override your `~/clearml.conf` with the proper credentials. To create new credentials go to:
```
Settings / Workspaces / App Credentials
```and click on `Create new credentials`, copy the credentials and paste them in your `~/clearml.conf`.
## Usage
To run the demo execute the following command:
```
python main.py
```You can use the following options to configure the experiment:
```
Options:
--project-name TEXT Name of the project [default: titanic-demo]
--train-size FLOAT Size of the training set [default: 0.9]
--epochs INTEGER Number of epochs [default: 100]
--batch-size INTEGER Batch size [default: 32]
--n-layer INTEGER Number of layers [default: 2]
--n-units INTEGER Number of units [default: 32]
```