Introducing auto-sklearn
scikit-learn (also known as sklearn) is a very popular ML library for Python development – so popular that it has its own memes:
Figure 3.40 – An ML meme
As part of this ecosystem and based on Efficient and Robust Automated Machine Learning by Feurer et al., auto-sklearn is an automated ML toolkit that performs algorithm selection and hyperparameter tuning using Bayesian optimization, meta-learning, and ensemble construction.
The toolkit is available on GitHub to be downloaded: github.com/automl/auto-sklearn.
auto-sklearn touts its ease of use for performing automated ML since it's a four-line automated ML solution:
Figure 3.41 – AutoML with auto-sklearn – getting started
If the preceding syntax looks familiar, then it's because this is how scikit-learn does predictions and therefore makes auto-sklearn one of the easiest libraries to use. auto-sklearn uses...
