- We will send in 10–14 business days.
/images/books/4062113/9780648783077.jpg)
- Author: Bob Mather
- Publisher: Bob Mather
- ISBN-10: 0648783073
- ISBN-13: 9780648783077
- Format: 14.8 x 21 x 1.4 cm, kieti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
Are you looking to learn more about Time Series, but struggling to find them in traditional Data Science textbooks?
This book is your answer.
Time Series is an exciting and important part of Data Analysis. Time Series Data is more readily available than most forms of data and answers questions that cross-sectional data struggle to do. It also has more real world application in the prediction of future events. However it is not generally found in a traditional data science toolkit. There is also limited centralized resources on the applications of Time Series, especially using traditional programming languages such as Python.
This book solves all these problems, and more. It starts off with basic concepts in Time Series, and switches to more advanced topics. It shows you how to set up Python from start, and goes through over 20 examples of applying both simple and advanced Time Series concepts with Python code.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 21d.06:35:53
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Bob Mather
- Publisher: Bob Mather
- ISBN-10: 0648783073
- ISBN-13: 9780648783077
- Format: 14.8 x 21 x 1.4 cm, kieti viršeliai
- Language: English English
Are you looking to learn more about Time Series, but struggling to find them in traditional Data Science textbooks?
This book is your answer.
Time Series is an exciting and important part of Data Analysis. Time Series Data is more readily available than most forms of data and answers questions that cross-sectional data struggle to do. It also has more real world application in the prediction of future events. However it is not generally found in a traditional data science toolkit. There is also limited centralized resources on the applications of Time Series, especially using traditional programming languages such as Python.
This book solves all these problems, and more. It starts off with basic concepts in Time Series, and switches to more advanced topics. It shows you how to set up Python from start, and goes through over 20 examples of applying both simple and advanced Time Series concepts with Python code.
Reviews