Introduces fundamental concepts of data science necessary for extracting useful information from data mining techniques, including envisioning the problem, applying data science techniques, and deploying results to improve decision making.
Annotation This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the ...
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems.
As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work.
You can't become an expert on a topic by consulting only Wikipedia, but certainly become smarter by starting there. you can Another very useful resource is Khan Academy. Most people think of Khan Academy as a set of videos that explain ...
... Toby Johnson, Katarzyna Bryc, Zoltan Kutalik, Adam R. Boyko, Adam Auton, Amit Indap, Karen S. King, Sven Bergmann, Matthew R. Nelson, Matthew Stephens, and Carlos D. Bustamante. Genes mirror geography within Europe.
To keep the book practical and applied, the authors feature a running case using a global airline business's customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout.
The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset.Ê WHAT WILL YOU LEARNÊÊ - Understand the multi-disciplinary nature of Data Science - Get familiar with ...
After reading this book, you too will learn how to use math and basic spreadsheet formulas to improve your business or, at the very least, how to trick senior executives into hiring you as their data scientist." —Ben Chestnut, Founder & ...
Let this book be your guide. Data Science For Dummies is for working professionals and students interested in transforming an organization's sea of structured, semi-structured, and unstructured data into actionable business insights.
In recent years, so-called “big data” has attracted the attention of companies and researchers. ... Since this problem is generally non-convex, a data-driven bounding strategy is developed to stabilize solutions and reduce relative gap ...