Deep Learning with scikit-learn

It has a good set of algorithms, supports sparse datasets, it is fast and has many utility functions, like cross-validation, grid search, etc. When it comes to advanced modeling, scikit-learn many times falls shorts. If you need Boosting, Neural Networks or t-SNE, it is better to avoid scikit-learn. There is MLPClassifier for classification and MLPRegressor for regression. While both have a rich set of arguments, there isn't an option to customize layers of a Neural Network (beyond setting the number of hidden units for each layer).