April 2018
Beginner to intermediate
282 pages
6h 52m
English
Scikit-learn has a great API for developing ML models and pipelines. Scikit-learn's API is very consistent and mature; if you are used to working with it, auto-sklearn (http://automl.github.io/auto-sklearn/stable/) will be just as easy to use since it's really a drop-in replacement for scikit-learn estimators.
Let's see a little example:
# Necessary importsimport autosklearn.classificationimport sklearn.model_selectionimport sklearn.datasetsimport sklearn.metricsfrom sklearn.model_selection import train_test_split# Digits dataset is one of the most popular datasets in machine learning community.# Every example in this datasets represents a 8x8 image of a digit.X, y = sklearn.datasets.load_digits(return_X_y=True)# Let's see the ...