Machine learning : a bayesian and optimization perspective

Machine learning : a bayesian and optimization perspective

Shranjeno v:

Bibliografske podrobnosti
Glavni avtor:	Theodoridis, Sergios. (Auteur)
Format:	E-Book
Jezik:	Anglais
Izdano:	London ; San Diego : Elsevier : Academic Press, 2015.
Teme:	Optimisation mathématique. Apprentissage automatique. Statistique bayésienne. Bayesian statistical decision theory. Machine learning. Mathematical optimization.
Autres localisations:	Voir dans le Sudoc
Online dostop:	Accès à l'E-book

Podobne knjige/članki

Optimization for machine learning
od: Sra, Suvrit (1976-....).
Izdano: (2011)

Optimization : a theory of necessary conditions
od: Neustadt, Lucien W. (1928-1972).
Izdano: (2015)

Bayesian Analysis with Python
od: Martin, Osvaldo.
Izdano: (2016)

Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications
od: Lantz, Brett.
Izdano: (2013)

Problèmes d'optimisation continue : avec corrigés et rappels de cours
od: Lafitte, Olivier (19..-....).

La formule du savoir : une philosophie unifiée du savoir fondée sur le théorème de Bayes
od: Hoang, Lê Nguyên (1987-....).
Izdano: (2018)

Bayesian Models : A Statistical Primer for Ecologists
od: Hobbs, N. Thompson.
Izdano: (2015)

Nature-inspired optimization algorithms
od: Yang, Xin-She (19..-....).
Izdano: (2020)

Machine learning for developers : uplift your regular applications with the power of statistics, analytics, and machine learning
od: Bonnin, Rodolfo.
Izdano: (2017)

Understanding uncertainty
od: Lindley, Dennis (1923-2013).
Izdano: (2014)

Réseaux bayésiens avec R
od: Denis, Jean-Baptiste (19..-....).
Izdano: (2014)

Machine learning for planetary science
od: Helbert, Joern.
Izdano: (2022)

Data science : fondamentaux et études de cas : machine learning avec Python et R
od: Biernat, Éric (19..-....).
Izdano: (2015)

Techniques d'optimisation.
od: Cerf, Max (1967-....).

Apache Mahout essentials : implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout
od: Withanawasam (Jayani).
Izdano: (2015)

Causes, probabilités, inférences
od: Drouet, Isabelle (1981-....; enseignante-chercheuse en philosophie des sciences).
Izdano: (2017)

Building Machine Learning Systems with Python : master the art of machine learning with Python and build effective machine learning systems with this intensive hands-on guide
od: Richert, Willi.
Izdano: (2013)

Practical machine learning in R
od: Nwanganga, Fred (19..-....).

Python machine learning
od: Lee, Wei-Meng (19..-....).

F# for machine learning essentials : get up and running with machine learning with F# in a fun and functional way
od: Mukherjee, Sudipta.
Izdano: (2016)

Machine Learning Algorithms : Reference guide for popular algorithms for data science and machine learning
od: Bonaccorso, Bonaccorso.
Izdano: (2017)

Adversial robustness for machine learning
od: Chen, Pin-Yu (19..-).

Inverse theory and applications in geophysics
od: Ždanov, Mihail Semenovič.
Izdano: (2015)

Self-Regularity : A New Paradigm for Primal-Dual Interior-Point Algorithms
od: Terlaky, Tamas.
Izdano: (2002)

Gaussian Processes for Machine Learning
od: Rasmussen, Carl Edward (1969-....).
Izdano: (2005)

Graph Machine Learning : Take graph data to the next level by applying machine learning techniques and algorithms
od: Stamile, Claudio (19..-....; chercheur en informatique).
Izdano: (2021)

Techniques d'optimisation.
od: Cerf, Max (1967-....).

Introduction to statistical machine learning
od: Sugiyama, Masashi.
Izdano: (2015)

Mastering .NET machine learning : master the art of machine learning with .NET and gain insight into real-world applications
od: Dixon, Jamie.
Izdano: (2016)

Réseaux bayésiens
od: Naïm, Patrick.
Izdano: (2007)

Developmental robotics : from babies to robots
od: Cangelosi, Angelo (1967-....).

Apprentissage machine, clé de l'intelligence artificielle : une introduction pour non-spécialistes
od: Gilleron, Rémi.

The Promise of Artificial Intelligence : Reckoning and Judgment
od: Smith, Brian Cantwell.
Izdano: (2019)

Méthodes numériques et optimisation : théorie et pratique pour l'ingénieur
od: Corriou, Jean-Pierre (1950-....).

Deep learning by example : a hands-on guide to implementing advanced machine learning algorithms and neural networks
od: Menshawy, Ahmed.
Izdano: (2018)

Deep learning with PyTorch : a practical approach to building neural network models using PyTorch
od: Subramanian, Vishnu (19..-....).
Izdano: (2018)

Apprentissage artificiel : concepts et algorithmes : de Bayes et Hume au Deep Learning
od: Barra, Vincent (19..-....; chercheur en informatique de modélisation).
Izdano: (2021)

R machine learning by example : understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully
od: Bali, Raghav (19..-....).
Izdano: (2016)

Métaheuristiques : recuit simulé, recherche avec tabous, recherche à voisinages variables, méthode GRASP, algorithmes évolutionnaires, fourmis artificielles, essaims particulaires et autres méthodes d'optimisation
Izdano: (2014)

Deep learning
od: Kelleher, John D. (1974-....).
Izdano: (2019)

Université catholique de l'Ouest - Bibliothèques - 3 place André Leroy - BP10808 - 49008 ANGERS Cedex 1