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Why SciPy? Fundamental algorithms. Broadly applicable. Foundational. Interoperable. Performant. Open source.
代替品と競合他社 scipy.org コンテンツ、トラフィック、構造に関して
Why NumPy? Powerful n-dimensional arrays. Numerical computing tools. Interoperable. Performant. Open source.
Matplotlib — Visualization with Python.
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Scipy Lecture Notes — Scipy lecture notes.
Scikit-learn: machine learning in Python — scikit-learn 0.16.1 documentation.
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Spark By Examples | Learn Spark Tutorial with Examples In this Apache Spark Tutorial, you will learn Spark with Scala code examples and every sample example explained here is available at Spark Examples Github Project for reference. All Spark examples provided in this Apache Spark Tutorials are basic, simple, easy to practice for beginners who
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The Python Package Index (PyPI) is a repository of software for the Python programming language.
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This cookbook contains more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly—without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project and includes a discussion of how and why the recipe works.
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The R graph gallery displays hundreds of charts made with R, always providing the reproducible code.