Go back

Python For Marketing Research And Analytics(1st Edition)

Authors:

Jason S. Schwarz , Chris Chapman , Elea McDonnell Feit

Free python for marketing research and analytics 1st edition jason s. schwarz , chris chapman , elea mcdonnell
10 ratings
Cover Type:Hardcover
Condition:Used

In Stock

Shipment time

Expected shipping within 2 Days
Access to 30 Million+ solutions Free
Ask 50 Questions from expert AI-Powered Answers
7 days-trial

Total Price:

$0

List Price: $55.24 Savings: $55.24(100%)
Access to 30 Million+ solutions
Ask 50 Questions from expert AI-Powered Answers 24/7 Tutor Help Detailed solutions for Python For Marketing Research And Analytics

Price:

$9.99

/month

Book details

ISBN: 3030497224, 978-3030497224

Book publisher: Springer

Get your hands on the best-selling book Python For Marketing Research And Analytics 1st Edition for free. Feed your curiosity and let your imagination soar with the best stories coming out to you without hefty price tags. Browse SolutionInn to discover a treasure trove of fiction and non-fiction books where every page leads the reader to an undiscovered world. Start your literary adventure right away and also enjoy free shipping of these complimentary books to your door.

Book Summary: This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.