Time Series 简明教程
Time Series Tutorial
时间序列是某个时期内一系列观测值。我们所有人每天都会遇到的时间序列的最简单的例子是全天、全周、全月或全年的温度变化。
A time series is a sequence of observations over a certain period. The simplest example of a time series that all of us come across on a day to day basis is the change in temperature throughout the day or week or month or year.
对时间数据的分析能够让我们深入了解变量如何随时间变化。
The analysis of temporal data is capable of giving us useful insights on how a variable changes over time.
本教程将教你如何借助各种统计和机器学习模型以详尽且易于理解的方式分析和预测时间序列数据！
This tutorial will teach you how to analyze and forecast time series data with the help of various statistical and machine learning models in elaborate and easy to understand way!
Audience
本教程适用于有兴趣了解时间序列和时间序列预测模型的人员。本教程结束后，你将对时间序列建模有很好的了解。
This tutorial is for the inquisitive minds who are looking to understand time series and time series forecasting models from scratch. At the end of this tutorial you will have a good understanding on time series modelling.
Prerequisites
本教程仅假设对 Python 语言有初步了解。虽然本教程是独立的，但如果你了解统计数学，将会有所裨益。
This tutorial only assumes a preliminary understanding of Python language. Although this tutorial is self-contained, it will be useful if you have understanding of statistical mathematics.
如果你刚接触 Python 或统计，我们建议你首先选一本基于这些主题的教程，然后再开始你的时间序列学习之旅。
If you are new to either Python or Statistics, we suggest you to pick up a tutorial based on these subjects first before you embark on your journey with Time Series.