Cantitate/Preț
Produs

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions

Autor Matt Taddy
en Limba Engleză Hardback – 18 aug 2019
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.


Use machine learning to understand your customers, frame decisions, and drive value  


The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science.  Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: 


• Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling
• Understand how use ML tools in real world business problems, where causation matters more that correlation
• Solve data science programs by scripting in the R programming language


Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science. 


Citește tot Restrânge

Preț: 18110 lei

Preț vechi: 22093 lei
-18% Nou

Puncte Express: 272

Preț estimativ în valută:
3205 3758$ 2814£

Carte tipărită la comandă

Livrare economică 30 ianuarie-10 februarie 26
Livrare express 27 decembrie 25 - 02 ianuarie 26 pentru 8432 lei

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781260452778
ISBN-10: 1260452778
Pagini: 416
Dimensiuni: 198 x 246 x 36 mm
Greutate: 0.73 kg
Editura: McGraw Hill Education
Colecția McGraw-Hill
Locul publicării:United States

Cuprins

Preface
Introduction
1 Uncertainty
2 Regression
3 Regularization
4 Classification
5 Experiments
6 Controls
7 Factorization
8 Text as Data
9 Nonparametrics
10 Artificial Intelligence
Bibliography
Index