Scikit-learn: Machine Learning Without Learning the Machinery

G. Varoquaux, L. Buitinck, Gilles Louppe, O. Grisel, Fabian Pedregosa, A. Mueller
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引用次数: 362

Abstract

Machine learning is a pervasive development at the intersection of statistics and computer science. While it can benefit many data-related applications, the technical nature of the research literature and the corresponding algorithms slows down its adoption. Scikit-learn is an open-source software project that aims at making machine learning accessible to all, whether it be in academia or in industry. It benefits from the general-purpose Python language, which is both broadly adopted in the scientific world, and supported by a thriving ecosystem of contributors. Here we give a quick introduction to scikit-learn as well as to machine-learning basics.
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Scikit-learn:不学习机器的机器学习
机器学习是统计学和计算机科学交叉领域的一项普遍发展。虽然它可以使许多与数据相关的应用受益,但研究文献的技术性质和相应的算法减慢了它的采用。Scikit-learn是一个开源软件项目,旨在让所有人都能使用机器学习,无论是在学术界还是在工业界。它受益于通用Python语言,Python语言在科学界被广泛采用,并得到了蓬勃发展的贡献者生态系统的支持。在这里,我们将快速介绍scikit-learn以及机器学习基础知识。
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