Statistical Learning.

Stochastic models, statistics and their applications = SMSA 2024, Delft, the Netherlands, March 13-15 / by: (Electronic resources)

Developments in statistical modelling by: (Electronic resources)

Applied statistical learning = with case studies in Stata / by: (Electronic resources)

Data driven model learning for engineers = with applications to univariate time series / by: (Electronic resources)

WAIC and WBIC with R Stan = 100 exercises for building logic / by: (Electronic resources)

Fundamentals of supervised machine learning = with applications in Python, R, and Stata / by: (Electronic resources)

Manifold learning = model reduction in engineering / by: (Electronic resources)

Causality for artificial intelligence = from a philosophical perspective / by: (Electronic resources)

An introduction to statistical data science = theory and models / by: (Electronic resources)

Decision mathematics, statistical learning and data mining = selected contributions from ICMSCT2023, Manila, Philippines, September 20-21 / by: (Electronic resources)

Recent trends and future challenges in learning from data by: (Electronic resources)

Statistical learning tools for electricity load forecasting by: (Electronic resources)

Classification and data science in the digital age by: (Electronic resources)

Practical statistical learning and data science methods = case studies from LISA 2020 Global Network, USA / by: (Electronic resources)

A first course in statistical learning = with data examples and Python code / by: (Electronic resources)

Data science, classification, and artificial intelligence for modeling decision making by: (Electronic resources)

New trends in functional statistics and related fields by: (Electronic resources)

Flight safety management = quantitative and AI approaches / by: (Electronic resources)

Beyond the T-Test by: (Electronic resources)

Supervised and unsupervised statistical data analysis by: (Electronic resources)

Foundations and advances of machine learning in official statistics by: (Electronic resources)

Multivariate statistics and machine learning in R for beginners = with applications in biology and medicine / by: (Electronic resources)

Sustainable statistical and data science methods and practices = reports from LISA 2020 Global Network, Ghana, 2022 / by: (Electronic resources)