Librería:
Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Calificación del vendedor: 5 de 5 estrellas
Vendedor de AbeBooks desde 27 de febrero de 2001
2021. 1st Edition. Hardcover. . . . . . N° de ref. del artículo V9780367894368
Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory.
Acerca del autor:
Osvaldo A. Martin is a Researcher at IMASL-CONICET in Argentina and the Department of Computer Science from Aalto University in Finland. He has a PhD in biophysics and structural bioinformatics. Over the years he has become increasingly interested in data analysis problems with a Bayesian flavor. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling.
Ravin Kumar is a Data Scientist at Google and previously worked at SpaceX and sweetgreen among other companies. He has an M.S in Manufacturing Engineering and a B.S in Mechanical Engineering. He found Bayesian statistics to be an excellent tool for modeling organizations and informing strategy. This interest in flexible statistical modeling led to a warm welcoming open source community which he is honored to be a member of now.
Junpeng Lao is a Data Scientist at Google. Prior to that he did his PhD and subsequently worked as a postdoc in Cognitive Neuroscience. He developed a fondness for Bayesian Statistics and generative modeling after working primarily with Bootstrapping and Permutation during his academic life.
Título: Bayesian Modeling and Computation in Python
Editorial: Taylor & Francis Ltd
Año de publicación: 2021
Encuadernación: Encuadernación de tapa dura
Condición: New
Edición: 1ª Edición
Librería: Feldman's Books, Menlo Park, CA, Estados Unidos de America
Hardcover. Condición: Fine. 1st Edition. Nº de ref. del artículo: 045764
Cantidad disponible: 1 disponibles