Dashboard to compare AutoML frameworks by exploring the results from runs of the OpenML AutoML Benchmark.
App Goal: View & compare performance of different AutoML frameworks, as benchmarked on the OpenML AutoML Benchmark
Target Audience: Data scientists
Industry: Any
GitHub: https://github.com/h2oai/wave-amlb
Actively Being Maintained: Yes
Comes with Demo Mode (pre-loaded data, models, results, etc.): Yes
Allows for Uploading and Using New Data: Yes
- Python 3.6+
- pip3
Follow the instructions here to download and run the latest Wave Server, a requirement for apps.
- Go to download the wave SDK for your platform
- Make sure to scroll down on the page to Assets. For MacOs select "darwin".
wave-0.12.0-darwin-amd64.tar.gz
- Extract your download:
- Make sure to run this command in the directory you downloaded the .tar.gz
tar -xzf wave-0.12.0-darwin-amd64.tar.gz
- Move it to a convenient location:
mv wave-0.12.0-darwin-amd64 <pathname>/wave
- check your $home/wave directory, the output should look like the following below:
.
├── demo
├── examples
├── readme.txt
├── test
├── waved
└── www
- Go to your wave directory:
cd wave
- Start the wave server by running:
./waved
When runninng the command, you may get an issue about "cannot open file because identity of developer can't be verified: - go to system preferences - security & privacy - general - you'll see a message about wave. select 'allow anyway' - attempt to run ./waved again
-
If step 6 worked you should be able to go to the following link:
- it's a spinning circle waiting for contact
- To run any Wave app, you need the Wave server up and running at all times.
$ git clone https://github.com/h2oai/wave-amlb
$ cd wave-amlb
$ make setup
$ source venv/bin/activate
After you set-up the python environment you can start the app by running
Note! this is in a separate terminal tab then where you ran './waved' command to start the wave server:
wave run src.app
Note! If you did not activate your virtual environment this will be:
./venv/bin/wave run src.app
Point your web browser to localhost:10101