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Data Science mit Python : das Handbuch für den Einsatz von IPython, Jupyter, NumPy, Pandas, Matplotlib, Scikit-Learn. mitp, Frechen, (2018)SciPy 1.0: Fundamental algorithms for scientific computing in Python, , , , , , , , , and 25 other author(s). Nature Methods, (March 2020)approxposterior: Approximate Posterior Distributions in Python., and . J. Open Source Softw., 3 (29): 781 (2018)Hierarchical Probabilistic Models for Group Anomaly Detection., , , , and . AISTATS, volume 15 of JMLR Proceedings, page 789-797. JMLR.org, (2011)mst_clustering: Clustering via Euclidean Minimum Spanning Trees.. J. Open Source Softw., 1 (1): 12 (2016)Hack Weeks as a model for Data Science Education and Collaboration., , , , , and . CoRR, (2017)Python Data Science Handbook. O'Reilly Media, Inc., (2016)Frequentism and Bayesianism: A Python-driven Primer.. SciPy, page 85-93. scipy.org, (2014)Scikit-learn: Machine Learning in Python., , , , , , , , , and 6 other author(s). J. Mach. Learn. Res., (2011)SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python., , , , , , , , , and 25 other author(s). CoRR, (2019)