@@ -16,6 +16,11 @@ Other packages useful for data analysis and machine learning.
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- `sklearn_pandas <https://github.com/paulgb/sklearn-pandas/ >`_ bridge for
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scikit-learn pipelines and pandas data frame with dedicated transformers.
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+ - `Scikit-Learn Laboratory
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+ <https://skll.readthedocs.org/en/latest/index.html> `_ A command-line
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+ wrapper around scikit-learn that makes it easy to run machine learning
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+ experiments with multiple learners and large feature sets.
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+
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- `theano <http://deeplearning.net/software/theano/ >`_ A CPU/GPU array
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processing framework geared towards deep learning research.
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@@ -26,14 +31,17 @@ Other packages useful for data analysis and machine learning.
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Extensions and Algorithms
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-------------------------
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- Libraries that provide a scikit-learn like interface and can be used with scikit-learn tools.
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+ Libraries that provide a scikit-learn like interface and can be used with
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+ scikit-learn tools.
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- `pylearn2 <http://deeplearning.net/software/pylearn2/ >`_ A deep learning and
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neural network library build on theano with scikit-learn like interface.
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- - `lightning <http://www.mblondel.org/lightning/ >`_ Fast state-of-the-art linear model solvers (SDCA, AdaGrad, SVRG, SAG, etc...).
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+ - `lightning <http://www.mblondel.org/lightning/ >`_ Fast state-of-the-art
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+ linear model solvers (SDCA, AdaGrad, SVRG, SAG, etc...).
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- - `Seqlearn <https://github.com/larsmans/seqlearn >`_ Sequence classification using HMMs or structured perceptron.
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+ - `Seqlearn <https://github.com/larsmans/seqlearn >`_ Sequence classification
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+ using HMMs or structured perceptron.
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- `HMMLearn <https://github.com/hmmlearn/hmmlearn >`_ Implementation of hidden
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markov models that was previously part of scikit-learn.
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