Languages
Suzuki, Joe.
Overview
| Works: | 0 works in 8 publications in 1 languages | |
|---|---|---|
Titles
Advanced methodologies for Bayesian networks = second International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015 : proceedings /
by:
Suzuki, Joe.; Ueno, Maomi.; SpringerLink (Online service)
(Electronic resources)
Sparse estimation with math and R = 100 exercises for building logic /
by:
Suzuki, Joe.; SpringerLink (Online service)
(Electronic resources)
Statistical learning with math and R = 100 exercises for building logic /
by:
Suzuki, Joe.; SpringerLink (Online service)
(Electronic resources)
Sparse estimation with math and python = 100 exercises for building logic /
by:
Suzuki, Joe.; SpringerLink (Online service)
(Electronic resources)
WAIC and WBIC with R Stan = 100 exercises for building logic /
by:
Suzuki, Joe.; SpringerLink (Online service)
(Electronic resources)
Kernel methods for machine learning with Math and Python = 100 exercises for building logic /
by:
Suzuki, Joe.; SpringerLink (Online service)
(Electronic resources)
Kernel methods for machine learning with Math and R = 100 exercises for building logic /
by:
Suzuki, Joe.; SpringerLink (Online service)
(Electronic resources)
Statistical learning with math and Python = 100 exercises for building logic /
by:
Suzuki, Joe.; SpringerLink (Online service)
(Electronic resources)
Subjects
Artificial intelligence
Data Structures and Information Theory.
Machine learning- Mathematics
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.
Artificial intelligence- Mathematics
Kernel functions.
Bayesian statistical decision theory
R (Computer program language)
Machine learning- Mathematics.
Computational Intelligence.
Artificial Intelligence.
Machine Learning.
Multivariate analysis.
Computer Science.
Probability and Statistics in Computer Science.
Logic, Symbolic and mathematical
Bayesian statistical decision theory.
Mathematical statistics.
Statistical Learning.