Suzuki, Joe.
Overview
Works: | 1 works in 9 publications in 1 languages |
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Titles
WAIC and WBIC with R Stan100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
Statistical learning with math and Python100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
Statistical learning with math and R :100 exercises for building logic /
by:
Suzuki, Joe.
(Language materials, printed)
Sparse estimation with math and python100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
Advanced methodologies for Bayesian networkssecond International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015 : proceedings /
by:
(1998 :); SpringerLink (Online service); Suzuki, Joe.; Ueno, Maomi.
(Electronic resources)
Kernel methods for machine learning with Math and R100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
Kernel methods for machine learning with Math and Python100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
Sparse estimation with math and R100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
Statistical learning with math and R100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
WAIC and WBIC with Python Stan100 exercises for building logic /
by:
SpringerLink (Online service); Suzuki, Joe.
(Electronic resources)
Subjects
Artificial intelligence
Data Structures and Information Theory.
Data Science.
Logic, Symbolic and mathematical.
Statistics, general.
Artificial Intelligence (incl. Robotics)
Algorithm Analysis and Problem Complexity.
Computation by Abstract Devices.
Database Management.
Information Systems Applications (incl. Internet)
Python (Computer program language)
Estimation theory.
Kernel functions.
Bayesian statistical decision theory
R (Computer program language)
Computational Intelligence.
Machine learning
Artificial Intelligence.
Machine Learning.
Multivariate analysis.
Computer Science.
Probability and Statistics in Computer Science.
Logic, Symbolic and mathematical
Machine learning.
Bayesian statistical decision theory.
Artificial intelligence.
Mathematical statistics.
Statistical Learning.