Machine Learning With Python 简明教程
Machine Learning with Python Tutorial
Machine Learning with Python Tutorial
机器学习（ML）基本上是计算机科学领域，计算机系统可以通过这种方式提供数据感知，就像人类一样。简而言之，ML 是一种人工智能，它通过使用算法或方法从原始数据中提取模式。ML 的主要重点是让计算机系统在没有明确编程或人工干预的情况下从经验中学习。
Machine Learning (ML) is basically that field of computer science with the help of which computer systems can provide sense to data in much the same way as human beings do. In simple words, ML is a type of artificial intelligence that extract patterns out of raw data by using an algorithm or method. The key focus of ML is to allow computer systems to learn from experience without being explicitly programmed or human intervention.
Audience
本教程对有兴趣于此主题或将此主题作为其课程一部分的研究生、毕业生和研究学生非常有用。读者可以是初学者或高级学习者。本教程已经为学生和专业人员准备，以便他们能快速提高。本教程是你机器学习之旅的垫脚石。
This tutorial will be useful for graduates, postgraduates, and research students who either have an interest in this subject or have this subject as a part of their curriculum. The reader can be a beginner or an advanced learner. This tutorial has been prepared for the students as well as professionals to ramp up quickly. This tutorial is a stepping stone to your Machine Learning journey.
Prerequisites
读者必须具备人工智能的基本知识。他们应该有良好的 Python 知识，并且应该了解其一些库，例如 NumPy、Pandas、Scikit-learn、Scipy 和 Matplotlib，以进行有效的数据处理和分析。
The reader must have basic knowledge of Artificial Intelligence. They should have a good knowledge of Python and some of its libraries such as NumPy, Pandas, Scikit-learn, Scipy and Matplotlib for effective data manipulation and analysis.
此外，读者应该对数学中的基础概念有深刻的理解，包括微积分、线性代数、概率、统计、算法和数据结构。
In addition, the readers should have a strong understanding of the fundamental concepts in mathematics including calculus, linear algebra, probability, statistics, algorithms and data structures.
如果你对这些概念中的任何一个还很陌生，我们建议你在深入研究本教程之前，去学习与这些主题相关的教程。
If you are new to any of these concepts, we recommend you to take up tutorials concerning these topics, before you dig further into this tutorial