Dask is an open-source Python library for parallel computing maintained by contributors across dozens of companies. The site describes uses including Dask DataFrames for pandas, parallel for loops, large arrays with NumPy and Xarray, and machine learning. It can run on a laptop or be deployed on resource managers such as Kubernetes or cloud.
ParaMonte
ParaMonte is a serial and parallel library of Monte Carlo routines for sampling mathematical density functions of arbitrary dimensions and machine learning algorithms for scientific inference. It is designed for interoperability with C, C++, Fortran, MATLAB and Python, and supports shared-memory OpenMP threads and MPI distributed communications.
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- Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C Source: github.com
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0Dask is an open-source Python library for parallel computing maintained by contributors across dozens of companies. The site describes uses including Dask DataFrames for pandas, parallel for loops, large arrays with NumPy and Xarray, and machine learning. It can run on a laptop or be deployed on resource managers such as Kubernetes or cloud.
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0Ruffus is an open-source computation pipeline library for Python, used in science and bioinformatics. It is designed to automate scientific and other analyses with a lightweight, standard-Python syntax, and can be installed from the Python Package Index.
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0Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing statistical graphics, and covers relational, distribution, categorical, regression and multi-plot grids, along with figure theming and color palettes.
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0Glue is a Python library for exploring relationships within and among related datasets. It provides linked statistical graphics such as scatter plots, histograms and 2D and 3D images, with selections in one graph propagating to others. It supports user-specified links across datasets and scripting through Python's scientific libraries.
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0astroML is a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, matplotlib and astropy, distributed under the 3-clause BSD license. It provides statistical and machine learning routines for analyzing astronomical data, loaders for open astronomical datasets, and examples of analyzing and visualizing datasets. The project was started in 2012 to accompany a textbook on statistics, data mining and machine learning in astronomy.
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0spaCy is a free open-source library for Natural Language Processing in Python. It features named entity recognition, part-of-speech tagging, dependency parsing and word vectors, supports over 75 languages and provides 84 trained pipelines for 25 languages.
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