A minimal Automatic Machine Learning solution with PyTorch
carefree-learn
carefree-learn is a minimal Automatic Machine Learning (AutoML) solution for tabular datasets based on PyTorch.
Carefree?
carefree-learn aims to provide CAREFREE usages for both users and developers.
User Side
import cflearn
import numpy as np
x = np.random.random([1000, 10])
y = np.random.random([1000, 1])
m = cflearn.make().fit(x, y)
Developer Side
import cflearn
import numpy as np
cflearn.register_model("wnd_full", pipes=[cflearn.PipeInfo("fcnn"), cflearn.PipeInfo("linear")])
x = np.random.random([1000, 10])
y = np.random.random([1000, 1])
m = cflearn.make("wnd_full").fit(x, y)
Please refer to Quick Start and Build Your Own Models for detailed information.
Why carefree-learn?
carefree-learn
- Provides a scikit-learn-like interface with much more ‘carefree’ usages, including:
- Automatically deals with data pre-processing.
- Automatically handles datasets saved in files (.txt, .csv).
- Supports Distributed Training, which