Scikit Learn 简明教程

Scikit Learn Tutorial

Scikit-learn (Sklearn) 是 Python 中机器学习最有用且最强大的库。它提供了一系列机器学习和统计建模的高效工具，包括分类、回归、聚类和降维，通过 Python 中的一致接口实现。这个库主要用 Python 编写，基于 NumPy、SciPy 和 Matplotlib 构建。

Scikit-learn (Sklearn) is the most useful and robust library for machine learning in Python. It provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction via a consistence interface in Python. This library, which is largely written in Python, is built upon NumPy, SciPy and Matplotlib.

Audience

本教程对毕业生、研究生和研究学生很有用，他们要么对这个机器学习主题感兴趣，要么把它作为课程的一部分。读者可以是初学者，也可以是高级学习者。

This tutorial will be useful for graduates, postgraduates, and research students who either have an interest in this Machine Learning subject or have this subject as a part of their curriculum. The reader can be a beginner or an advanced learner.

Prerequisites

读者必须具备机器学习的基础知识。他还/她也应该了解 Python、NumPy、Scipy 和 Matplotlib。如果您对这些概念中的任何一个感到陌生，我们建议您在进一步深入本教程之前，学习有关这些主题的教程。

The reader must have basic knowledge about Machine Learning. He/she should also be aware about Python, NumPy, Scipy, Matplotlib. If you are new to any of these concepts, we recommend you take up tutorials concerning these topics, before you dig further into this tutorial.