- We will send in 10–14 business days.
/images/books/12994934/9783030870225.jpg)
- Author: Walter R Paczkowski
- Publisher: Springer
- ISBN-10: 3030870227
- ISBN-13: 9783030870225
- Format: 15.6 x 23.4 x 2.4 cm, kieti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of:
1. statistical, econometric, and machine learning techniques;
2. data handling capabilities;
3. at least one programming language.
Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 22d.08:25:37
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Walter R Paczkowski
- Publisher: Springer
- ISBN-10: 3030870227
- ISBN-13: 9783030870225
- Format: 15.6 x 23.4 x 2.4 cm, kieti viršeliai
- Language: English English
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of:
1. statistical, econometric, and machine learning techniques;
2. data handling capabilities;
3. at least one programming language.
Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.
Reviews