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https://github.com/mljar/mljar-api-python
A simple python wrapper over MLJAR API.
https://github.com/mljar/mljar-api-python
machine-learning machine-learning-api mljar-api-python prediction-algorithm predictive-analytics predictive-modeling python
Last synced: about 1 month ago
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A simple python wrapper over MLJAR API.
- Host: GitHub
- URL: https://github.com/mljar/mljar-api-python
- Owner: mljar
- License: apache-2.0
- Archived: true
- Created: 2016-09-06T09:09:38.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2022-06-21T21:14:53.000Z (over 2 years ago)
- Last Synced: 2024-09-15T23:38:47.458Z (3 months ago)
- Topics: machine-learning, machine-learning-api, mljar-api-python, prediction-algorithm, predictive-analytics, predictive-modeling, python
- Language: Python
- Homepage: https://docs.mljar.com/
- Size: 106 KB
- Stars: 42
- Watchers: 11
- Forks: 10
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome - mljar-api-python - A simple python wrapper over MLJAR API. (Python)
README
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# mljar-api-python
A simple python wrapper over mljar API. It allows MLJAR users to create Machine Learning models with few lines of code:
```python
from mljar import Mljar
model = Mljar(project='My awesome project', experiment='First experiment')
model.fit(X,y)
model.predict(X)
```
That's all folks! Yeah, I know, this makes Machine Learning super easy! You can use this code for following Machine Learning tasks:
* Binary classification (your target has only two unique values)
* Regression (your target value is continuous)
* More is coming soon!
## How to install
You can install mljar with **pip**:
pip install -U mljar
or from source code:
python setup.py install
## How to use it
1. Create an account at mljar.com and login.
2. Please go to your users settings (top, right corner).
3. Get your token, for example 'exampleexampleexample'.
4. Set environment variable `MLJAR_TOKEN` with your token value:
```
export MLJAR_TOKEN=exampleexampleexample
```
5. That's all, you are ready to use MLJAR in your python code!
## What's going on?
* This wrapper allows you to search through different Machine Learning algorithms and tune each of the algorithm.
* By searching and tuning ML algorithm to your data you will get very accurate model.
* By calling method `fit` from `Mljar class` you create new project and start experiment with models training.
All your results will be accessible from your mljar.com account - this makes Machine Learning super easy and
keeps all your models and results in beautiful order. So, you will never miss anything.
* All computations are done in MLJAR Cloud, they are executed in parallel. So after calling `fit` method you can switch
your computer off and MLJAR will do the job for you!
* I think this is really amazing! What do you think? Please let us know at `[email protected]`.
## Examples
The examples are [here!](https://github.com/mljar/mljar-examples).
## Testing
To run tests with command:
```
python -m tests.run
```