Prikupljanje sredstava 15. septembra 2024 – 1. oktobra 2024 O prikupljanju novca

The Elements of Statistical Learning: Data Mining,...

Main
Computers - Cybernetics
The Elements of Statistical Learning:...

The Elements of Statistical Learning: Data Mining, Inference, and Prediction.

Trevor Hastie, Robert Tibshirani, Jerome Friedman

5.0 / 0

Koliko vam se sviđa ova knjiga?

Kakav je kvalitet fajla?

Preuzmite knjigu radi procene kvaliteta

Kakav je kvalitet preuzetih fajlova?

Kategorije:

Computers - Cybernetics

Godina:

2013

Izdanje:

2

Izdavač:

Springer

Jezik:

english

Strane:

764

Serije:

Springer Series in Statistics

Fajl:

PDF, 12.69 MB

IPFS:

,

english, 2013

Čitati Online

Konvertovanje u je u toku

Konvertovanje u nije uspešno

Možda će vas zanimati

Trevor Hastie, Robert Tibshirani, Jerome Friedman — The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

George Casella, Roger L. Berger — Statistical Inference

Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola — Dive into Deep Learning

Lijun Wang — 统计学习基础 The Elements of Statistical Learning

Kevin P. Murphy [Murphy, Kevin P.] — Machine Learning: A Probabilistic Perspective

David J. Abner — The ETF Handbook

Linoff G.S. Berry M.J. — Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management 3rd Ed. 2011

Sebastian Raschka, Vahid Mirjalili — Python Machine Learning

Michael Nielsen — Neural Networks and Deep Learning

Trevor Hastie, Robert Tibshirani, Jerome Friedman — The Elements of Statistical Learning : Data Mining, Inference and Prediction

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Trevor Hastie, Robert Tibshirani, Jerome Friedman — The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd edition) (12print 2017)

Kaare Brandt Petersen, Michael Syskind Pedersen — The Matrix Cookbook

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Sutton, Richard S., Barto, Andrew G. — Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)

Richard Mcelreath — Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science)

Trevor Hastie, Jerome Friedman, Robert Tibshirani (auth.) — The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Christopher M. Bishop — Pattern Recognition and Machine Learning

Trevor Hastie, Robert Tibshirani, Jerome Friedman — The elements of statistical learning: Data mining, inference, and prediction

Trevor Hastie, Robert Tibshirani, Jerome Friedman — The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Trevor Hastie, Robert Tibshirani, Jerome Friedman — The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Glenn J. Myatt, Wayne P. Johnson — Making sense of data II: a practical guide to data visualization, advanced data mining methods, and applications

Carlo Vercellis — Business Intelligence: Data Mining and Optimization for Decision Making

Geof H. Givens, Jennifer A. Hoeting(auth.) — Computational Statistics, Second Edition

Sanjeev Kulkarni, Gilbert Harman — An Elementary Introduction to Statistical Learning Theory

Vladimir N. Vapnik — Statistical Learning Theory

Daniel T. Larose — Data Mining Methods and Models

Nello Cristianini, John Shawe-Taylor — An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

Barber, D — Bayesian reasoning and machine learning

G. A. Young, R. L. Smith — Essentials of Statistical Inference

Steven L. Tanimoto — Elements of Artificial Intelligence: An Introduction Using Lisp

Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani — An Introduction To Statistical Learning: With Applications In R (Second Edition)

Bradley Efron, Trevor Hastie — Computer Age Statistical Inference: Algorithms, Evidence, and Data Science

Marcos M. López de Prado — Machine Learning for Asset Managers

Joseph K. Blitzstein, Jessica Hwang — Introduction to Probability, Second Edition

Robert V. Hogg, Joeseph McKean, Allen T. Craig — Introduction to Mathematical Statistics, 8th Global Edition

Gelman A., Carlin J.B. — Bayesian data analysis

Christian Robert, George Casella (auth.) — Introducing Monte Carlo Methods with R

Vladimir Vapnik — The Nature Of Statistical Learning

Sarah Boslaugh — Statistics in a Nutshell : [a desktop quick reference]

Andreas C. Müller, Sarah Guido — Introduction to Machine Learning with Python: A Guide for Data Scientists

Kuhn, Max;Johnson, Kjell — Applied Predictive Modeling

Najčešći pojmovi

Povezani Spiskovi knjiga