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所在平台: Udemy |
课程主页: https://www.udemy.com/course/complete-practical-time-series-forecasting-in-python/
课程评论：没有评论
**课程名称：** 掌握 Python 时间序列预测 **课程概述：** 本课程是关于数据科学领域中时间序列分析与预测的深度学习，该领域在当今工业界有着广泛的应用，许多公司都在寻找具备此技能的数据科学家。课程将全面涵盖预测和分析的各种建模技术。 * **Python 基础：** 从 Python 编程入门，这是掌握时间序列分析必备的技能。 * **时间序列理论：** 深入探索时间序列的基本理论，为后续的建模奠定坚实基础。 * **Python 库实践：** 熟练运用包括 pandas（强大的时间序列功能）、NumPy、matplotlib、statsmodels、Sklearn 和 ARCH 在内的核心 Python 库。 * **经典模型掌握：** 学习并掌握最常用的时间序列模型，包括： * 加法模型 (Additive Model) * 乘法模型 (Multiplicative Model) * AR (自回归模型) * 简单移动平均 (Simple Moving Average) * 加权移动平均 (Weighted Moving Average) * 指数移动平均 (Exponential Moving Average) * ARMA (自回归-移动平均模型) * ARIMA (自回归积分移动平均模型) * Auto ARIMA * **解决疑难：** 课程旨在彻底解决学员在时间序列学习中遇到的所有疑难问题。 * **丰富材料：** 提供大量附加学习资料，包括记事本文件和课程笔记。 本课程是帮助您彻底理解时间序列的理想选择。
Welcome to Mastering Time Series Forecasting in PythonTime series analysis and forecasting is one of the areas of Data Science and has a wide variety of applications in the industries in the current world. Many industries looking for a Data Scientist with these skills. This course covers all types of modeling techniques for forecasting and analysis. We start with programming in Python which is the essential skill required and then we will exploring the fundamental time series theory to help you understand the modeling that comes afterward.Then throughout the course, we will work with a number of Python libraries, providing you with complete training. We will use the powerful time-series functionality built into pandas, as well as other fundamental libraries such as NumPy, matplotlib, statsmodels, Sklearn, and ARCH.With these tools we will master the most widely used models out there:Additive ModelMultiplicative ModelAR (autoregressive model)Simple Moving AverageWeighted Moving AverageExponential Moving AverageARMA (autoregressive-moving-average model)ARIMA (autoregressive integrated moving average model)Auto ARIMAWe know that time series is one of those topics that always leaves some doubts.Until now.This course is exactly what you need to comprehend the time series once and for all. Not only that, but you will also get a ton of additional materials - notebooks files, course notes - everything is included.
