你好! Shipping to Taiwan with premium packaging for just NT$300 

Ship to
Taiwan
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Data Driven Model Learning for Engineers. With Applications to Univariate Time Series
Type
Physical Book
Publisher
Author
Year
2023
Language
English
Pages
224
Format
Paperback
Dimensions
23.4x15.6x1.2 cm
ISBN13
9783031316371

Data Driven Model Learning for Engineers. With Applications to Univariate Time Series

Guillaume Mercère (Author) · Springer · Paperback

Data Driven Model Learning for Engineers. With Applications to Univariate Time Series - Guillaume Mercère

Cheaper New Book Imported to Taiwan
Delivery: 30 Nov - 11 Dec Shipping: 11 to 15 business days.
NT$ 2,061
Faster New Book Imported to Taiwan
Delivery: 20 Nov - 30 Nov Shipping: 5 to 6 business days.
NT$ 2,166
NT$ 2,061

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Data Driven Model Learning for Engineers. With Applications to Univariate Time Series"

The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail. 
As applications of data-driven model learning become widespread in society, engineers need to understand its underlying principles, then the skills to develop and use the resulting data-driven model learning solutions. After reading this book, the users will have acquired the background, the knowledge and confidence to (i) read other model learning textbooks more easily, (ii) use linear algebra and statistics for data analysis and modeling, (iii) explore other fields of applications where model learning from data plays a central role. Thanks to numerous illustrations and simulations, this textbook will appeal to undergraduate and graduate students who need a first course in data-driven model learning. It will also be useful for practitioners, thanks to the introduction of easy-to-implement recipes dedicated to stationary time series model learning. Only a basic familiarity with advanced calculus, linear algebra and statistics is assumed, making the material accessible to students at the advanced undergraduate level.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews