The Art of Data-Driven Business (eBook)
314 Seiten
Packt Publishing (Verlag)
978-1-80461-873-8 (ISBN)
One of the most valuable contributions of data science is toward helping businesses make the right decisions. Understanding this complicated confluence of two disparate worlds, as well as a fiercely competitive market, calls for all the guidance you can get.
The Art of Data-Driven Business is your invaluable guide to gaining a business-driven perspective, as well as leveraging the power of machine learning (ML) to guide decision-making in your business. This book provides a common ground of discussion for several profiles within a company.
You'll begin by looking at how to use Python and its many libraries for machine learning. Experienced data scientists may want to skip this short introduction, but you'll soon get to the meat of the book and explore the many and varied ways ML with Python can be applied to the domain of business decisions through real-world business problems that you can tackle by yourself. As you advance, you'll gain practical insights into the value that ML can provide to your business, as well as the technical ability to apply a wide variety of tried-and-tested ML methods.
By the end of this Python book, you'll have learned the value of basing your business decisions on data-driven methodologies and have developed the Python skills needed to apply what you've learned in the real world.
Learn how to make the right decisions for your business with the help of Python recipes and the expertise of data leadersKey FeaturesLearn and practice various clustering techniques to gather market insights Explore real-life use cases from the business world to contextualize your learningWork your way through practical recipes that will reinforce what you have learnedBook DescriptionOne of the most valuable contributions of data science is toward helping businesses make the right decisions. Understanding this complicated confluence of two disparate worlds, as well as a fiercely competitive market, calls for all the guidance you can get.The Art of Data-Driven Business is your invaluable guide to gaining a business-driven perspective, as well as leveraging the power of machine learning (ML) to guide decision-making in your business. This book provides a common ground of discussion for several profiles within a company.You'll begin by looking at how to use Python and its many libraries for machine learning. Experienced data scientists may want to skip this short introduction, but you'll soon get to the meat of the book and explore the many and varied ways ML with Python can be applied to the domain of business decisions through real-world business problems that you can tackle by yourself. As you advance, you'll gain practical insights into the value that ML can provide to your business, as well as the technical ability to apply a wide variety of tried-and-tested ML methods.By the end of this Python book, you'll have learned the value of basing your business decisions on data-driven methodologies and have developed the Python skills needed to apply what you've learned in the real world.What you will learnCreate effective dashboards with the seaborn libraryPredict whether a customer will cancel their subscription to a serviceAnalyze key pricing metrics with pandasRecommend the right products to your customersDetermine the costs and benefits of promotionsSegment your customers using clustering algorithmsWho this book is forThis book is for data scientists, machine learning engineers and developers, data engineers, and business decision makers who want to apply data science for business process optimization and develop the skills needed to implement data science projects in marketing, sales, pricing, customer success, ad tech, and more from a business perspective. Other professionals looking to explore how data science can be used to improve business operations, as well as individuals with technical skills who want to back their technical proposal with a strong business case will also find this book useful.
Erscheint lt. Verlag | 2.12.2022 |
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Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
Mathematik / Informatik ► Informatik ► Theorie / Studium | |
Mathematik / Informatik ► Informatik ► Web / Internet | |
ISBN-10 | 1-80461-873-X / 180461873X |
ISBN-13 | 978-1-80461-873-8 / 9781804618738 |
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