Probability for Statistics and Machine Learning Fundamentals and Advanced Topics /
This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and num...
Κύριος συγγραφέας: | DasGupta, Anirban (Συγγραφέας) |
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Συγγραφή απο Οργανισμό/Αρχή: | SpringerLink (Online service) |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
New York, NY :
Springer New York : Imprint: Springer,
2011.
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Σειρά: | Springer Texts in Statistics,
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Παρόμοια τεκμήρια
-
Applied Probability
ανά: Lange, Kenneth
Έκδοση: (2010) -
Asymptotic Theory of Statistics and Probability
ανά: DasGupta, Anirban
Έκδοση: (2008) -
Multiscale Modeling A Bayesian Perspective /
ανά: Ferreira, Marco A. R., κ.ά.
Έκδοση: (2007) -
Inference on the Hurst Parameter and the Variance of Diffusions Driven by Fractional Brownian Motion
ανά: Berzin, Corinne, κ.ά.
Έκδοση: (2014) -
Dependence in Probability and Statistics
Έκδοση: (2006)