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The art of data-driven business : transform your organization into a data-driven one with the power of python machine learning / Alan Bernardo Palacio.

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Format:
Book
Author/Creator:
Palacio, Alan Bernardo, author.
Language:
English
Subjects (All):
Electronic data processing.
Decision making--Data processing.
Decision making.
Punched card systems.
Physical Description:
1 online resource (314 pages)
Edition:
First edition.
Place of Publication:
2022.
Birmingham : Packt Publishing, [2022]
Biography/History:
Palacio Alan Bernardo: Alan Bernardo Palacio is a data scientist and an engineer with vast experience in different engineering fields. His focus has been the development and application of state-of-the-art data products and algorithms in several industries. He has worked for companies such as Ernst and Young, Globant, and now holds a data engineer position at Ebiquity Media helping the company to create a scalable data pipeline. Alan graduated with a Mechanical Engineering degree from the National University of Tucuman in 2015, participated as the founder in startups, and later on earned a Master's degree from the faculty of Mathematics in the Autonomous University of Barcelona in 2017. Originally from Argentina, he now works and resides in the Netherlands.
Summary:
The Art of Data-Driven Business is a practical guide to understanding the intricacies of powering your business decisions with machine learning algorithms backed by the might of Python. The techniques you'll learn in this book will enable you to make the best possible decisions based on a data-driven approach.
Contents:
Table of Contents Data Analysis and Visualization with Pandas and Seaborn Machine Learning with Sci-Kit Learn Market Trend Insights Customer and Product Segmentation Estimating Customer Satisfaction Predicting Churn and Conversion Performing Pricing Analytics Forecasting Sales and Recommending Products Optimizing Promotion and Stock Improving Digital Marketing Strategy Interviewing Business Leaders.
Notes:
Description based on publisher supplied metadata and other sources.
Description based on print version record.
ISBN:
9781804618738
180461873X
OCLC:
1353733724

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