Kazan Federal University Digital Repository

Data science for marketing analytics: a practical guide to forming a killer marketing strategy through data analysis with Python/ Mirza Rahim Baig, Gururajan Govindan, Vishwesh Ravi Shrimali.

Show simple item record

dc.contributor.author Baig Mirza Rahim
dc.contributor.author Govindan Gururajan
dc.contributor.author Shrimali Vishwesh Ravi
dc.date.accessioned 2024-01-26T21:40:16Z
dc.date.available 2024-01-26T21:40:16Z
dc.date.issued 2021
dc.identifier.citation Baig. Data science for marketing analytics: a practical guide to forming a killer marketing strategy through data analysis with Python: Second edition. - 1 online resource - URL: https://libweb.kpfu.ru/ebsco/pdf/3030701.pdf
dc.identifier.isbn 9781800563889
dc.identifier.isbn 1800563884
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/178649
dc.description.abstract Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language. Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learn: Load, clean, and explore sales and marketing data using pandas; Form and test hypotheses using real data sets and analytics tools; Visualize patterns in customer behavior using Matplotlib; Use advanced machine learning models like random forest and SVM; Use various unsupervised learning algorithms for customer segmentation; Use supervised learning techniques for sales prediction; Evaluate and compare different models to get the best outcomes; Optimize models with hyperparameter tuning and SMOTE. Who this book is for: This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.
dc.language English
dc.language.iso en
dc.subject.other Consumer behavior -- Data processing.
dc.subject.other Marketing -- Data processing.
dc.subject.other Python (Computer program language)
dc.subject.other Consumer behavior -- Data processing.
dc.subject.other Marketing -- Data processing.
dc.subject.other Python (Computer program language)
dc.subject.other Electronic books.
dc.title Data science for marketing analytics: a practical guide to forming a killer marketing strategy through data analysis with Python/ Mirza Rahim Baig, Gururajan Govindan, Vishwesh Ravi Shrimali.
dc.type Book
dc.description.pages 1 online resource
dc.collection Электронно-библиотечные системы
dc.source.id EN05CEBSCO05C1863


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account

Statistics