Machine Learning for Time Series Forecasting with Python (Paperback)

Lazzeri, Francesca

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商品描述

Learn how to apply the principles of machine learning to time series modeling with this indispensable resource

Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling.

Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting.

Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to:

  • Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality
  • Prepare time series data for modeling
  • Evaluate time series forecasting models' performance and accuracy
  • Understand when to use neural networks instead of traditional time series models in time series forecasting

Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts.

Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.

 

 

商品描述(中文翻譯)

學習如何將機器學習原則應用於時間序列建模,這是一本不可或缺的資源。

《使用Python進行時間序列預測的機器學習》是對金融、行銷、教育和醫療等決策中最關鍵的元素之一——時間序列建模的深入且直接的探討。

儘管時間序列預測的重要性,但很少有商業分析師熟悉將機器學習應用於時間序列建模的能力和效用。作者Francesca Lazzeri是一位傑出的機器學習科學家和經濟學家,通過提供讀者全面且易於理解的解釋和處理機器學習應用於時間序列預測的方法來補充這一不足。

本書針對沒有或幾乎沒有時間序列預測或機器學習經驗的讀者,全面涵蓋了以下所有主題:

- 理解時間序列預測概念,如穩定性、預測範圍、趨勢和季節性
- 為建模準備時間序列數據
- 評估時間序列預測模型的性能和準確性
- 理解何時在時間序列預測中使用神經網絡而不是傳統時間序列模型

《使用Python進行時間序列預測的機器學習》充滿了真實世界的例子、資源和具體策略,幫助讀者探索和轉換數據,並開發可用的實用時間序列預測。

這本書非常適合初級數據科學家、商業分析師、開發人員和研究人員,是機器學習應用於時間序列建模的基本和高級概念的寶貴指南。

作者簡介

FRANCESCA LAZZERI is an accomplished economist who works with machine learning, artificial intelligence, and applied econometrics. She works at Microsoft as a data scientist and machine learning scientist to develop a portfolio of machine learning services. She is a sought-after speaker and has given popular talks at AI conferences and academic seminars at Berkeley, Harvard, and MIT.

作者簡介(中文翻譯)

FRANCESCA LAZZERI是一位經驗豐富的經濟學家,專注於機器學習、人工智慧和應用計量經濟學。她在微軟擔任數據科學家和機器學習科學家,開發機器學習服務的產品組合。她是一位備受追捧的演講者,在人工智慧會議和伯克利、哈佛和麻省理工學院的學術研討會上發表過受歡迎的演講。