Machine learning - Mathematics.

Linear algebra and optimization with applications to machine learning / by: (Language materials, printed)

Black box optimization, machine learning, and no-free lunch theorems by: (Electronic resources)

Mathematical foundations for data analysis by: (Electronic resources)

Algorithmic aspects of machine learning by: (Electronic resources)

Kernel methods for machine learning with Math and R100 exercises for building logic / by: (Electronic resources)

Kernel methods for machine learning with Math and Python100 exercises for building logic / by: (Electronic resources)

Alternating direction method of multipliers for machine learning by: (Electronic resources)

Probabilistic numericscomputation as machine learning / by: (Electronic resources)

Random matrix methods for machine learning by: (Electronic resources)

Essential math for data science :take control of your data with fundamental linear algebra, probability, and statistics / by: (Language materials, printed)

Elements of dimensionality reduction and manifold learning by: (Electronic resources)

Fundamental mathematical concepts for machine learning in science by: (Electronic resources)

Mathematical introduction to data science by: (Electronic resources)

Advanced techniques in optimization for machine learning and imaging by: (Electronic resources)

Variational and information flows in machine learning and optimal transport by: (Electronic resources)