Springer Series in the Data Sciences

Michele Gallo and Others
Series • 10 Books • Mathematics
Statistical Inference and Machine Learning for Big Data Statistical Inference and Machine Learning for Big Data
Statistical Inference and Machine Learning for Big Data
Mayer Alvo
Statistics in the Public Interest Statistics in the Public Interest
Statistics in the Public Interest
Alicia L. Carriquiry, Judith M. Tanur & William F. Eddy
Multivariate Data Analysis on Matrix Manifolds Multivariate Data Analysis on Matrix Manifolds
Multivariate Data Analysis on Matrix Manifolds
Nickolay Trendafilov & Michele Gallo
Statistics with Julia Statistics with Julia
Statistics with Julia
Yoni Nazarathy & Hayden Klok
Data Science for Public Policy Data Science for Public Policy
Data Science for Public Policy
Jeffrey C. Chen, Edward A. Rubin & Gary J. Cornwall
Mathematical Foundations for Data Analysis Mathematical Foundations for Data Analysis
Mathematical Foundations for Data Analysis
Jeff M. Phillips
First-order and Stochastic Optimization Methods for Machine Learning First-order and Stochastic Optimization Methods for Machine Learning
First-order and Stochastic Optimization Methods for Machine Learning
Guanghui Lan
Cohesive Subgraph Computation over Large Sparse Graphs Cohesive Subgraph Computation over Large Sparse Graphs
Cohesive Subgraph Computation over Large Sparse Graphs
Lijun Chang & Lu Qin
A Parametric Approach to Nonparametric Statistics A Parametric Approach to Nonparametric Statistics
A Parametric Approach to Nonparametric Statistics
Mayer Alvo & Philip L. H. Yu
Lectures on the Nearest Neighbor Method Lectures on the Nearest Neighbor Method
Lectures on the Nearest Neighbor Method
Gérard Biau & Luc Devroye