Time Series 简明教程
Time Series - Programming Languages
对于用户来说，基本了解任何一种编程语言对于解决或开发机器学习问题都是至关重要的。对于希望从事机器学习工作的任何人，下面给出了他们首选的编程语言列表——
A basic understanding of any programming language is essential for a user to work with or develop machine learning problems. A list of preferred programming languages for anyone who wants to work on machine learning is given below −
Python
它是一种高级解释性编程语言，编码快速且容易。Python 可以遵循过程式或面向对象编程范例。各种库的存在让实现复杂的程序变得更简单。在本教程中，我们将用 Python 编码，并且将在后续章节中讨论对时间序列建模有用的相应库。
It is a high-level interpreted programming language, fast and easy to code. Python can follow either procedural or object-oriented programming paradigms. The presence of a variety of libraries makes implementation of complicated procedures simpler. In this tutorial, we will be coding in Python and the corresponding libraries useful for time series modelling will be discussed in the upcoming chapters.
R
与 Python 类似，R 是一种解释多范例语言，支持统计计算和图形。各种包让在 R 中实现机器学习建模变得更容易。
Similar to Python, R is an interpreted multi-paradigm language, which supports statistical computing and graphics. The variety of packages makes it easier to implement machine learning modelling in R.
Java
它是一种解释面向对象编程语言，以大量可用的包和复杂的数据可视化技术而闻名。
It is an interpreted object-oriented programming language, which is widely famous for a large range of package availability and sophisticated data visualization techniques.
C/C++
这些是编译语言，也是最古老的两种编程语言。在已有的应用程序中纳入 ML 能力时人们常常选择这些语言，因为它们能让您轻松自定义 ML 算法的实现。
These are compiled languages, and two of the oldest programming languages. These languages are often preferred to incorporate ML capabilities in the already existing applications as they allow you to customize the implementation of ML algorithms easily.
MATLAB
MATrix LABoratory 是一种多范例语言，为使用矩阵提供功能。它允许对复杂问题进行数学运算。它主要用于数值运算，但一些包也允许图形多域模拟和基于模型的设计。
MATrix LABoratory is a multi-paradigm language which gives functioning to work with matrices. It allows mathematical operations for complex problems. It is primarily used for numerical operations but some packages also allow the graphical multi-domain simulation and model-based design.
用于机器学习问题的其他首选编程语言包括 JavaScript、LISP、Prolog、SQL、Scala、Julia、SAS 等。
Other preferred programming languages for machine learning problems include JavaScript, LISP, Prolog, SQL, Scala, Julia, SAS etc.