The Data Science Design Manual

• Κύριος συγγραφέας: Skiena, Steven S. (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: Texts in Computer Science,
• Θέματα: Computer science.; Big data.; Data mining.; Pattern recognition.; Mathematics.; Visualization.; Statistics.; Computer Science.; Data Mining and Knowledge Discovery.; Pattern Recognition.; Big Data/Analytics.; Statistics and Computing/Statistics Programs.

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and...

Πίνακας περιεχομένων:

• What is Data Science?
• Mathematical Preliminaries
• Data Munging
• Scores and Rankings
• Statistical Analysis
• Visualizing Data
• Mathematical Models
• Linear Algebra
• Linear and Logistic Regression
• Distance and Network Methods
• Machine Learning
• Big Data: Achieving Scale.