Risultati di ricerca
An Introduction to Statistical Learning. As the scale and scope of data collection continue to increase across virtually all fields, statistical learning has become a critical toolkit for anyone who wishes to understand data. An Introduction to Statistical Learning provides a broad and less technical treatment of key topics in statistical learning.
Daniela Witten. Professor, Department of Biostatistics; Department of Statistics. Artificial intelligence, Big data, Information science. 206-616-7182 / dwitten@uw.edu. Web / Twitter / Pronouns: she/her. Expertise: Machine learning for big data, with applications to genomics, neuroscience, and other fields. Daniela Witten’s research involves ...
Department of Statistics B-323, Padelford Hall, Box 354322, Seattle WA 98195-4322 . Department of Biostatistics Room 332, Hans Rosling Center, Box 351617, Seattle WA 98195-1617
The Big Data Blog: Daniela Witten AAAS news, 03/17/2014. How Crunching Big Data Could Save Our Lives KUOW, 01/28/2014. Biostatistician Named to Forbes' List of Top Scientists for Third Straight Year SPH News, 01/10/2014. Three From UW Named Sloan Research Fellows The Daily, 03/05/2013. SPH Statistician Named One of Forbes’ Rising Stars SPH ...
Daniela Mottel Witten est une biostatisticienne américaine. Elle est professeure et titulaire de la Dorothy Gilford Endowed Chair of Mathematical Statistics à l' Université de Washington 1, 2. Ses recherches portent sur l'utilisation de l' apprentissage automatique pour la synthèse de données multidimensionnelles (en) .
Daniela Witten. Daniela M. Witten es una bioestadística americana. Es profesora y posee una cátedra dotada ( endowed chair) Dorothy Gilford de Estadística Matemática en la Universidad de Washington. 1 2 Su campo de investigación es el uso del aprendizaje automático aplicado a los datos multidimensionales.
Daniela Witten is a statistician with broad interests in statistical machine learning and high-dimensional data. She uses tools from convex optimization to tackle large-scale problems, and she is particularly interested in developing statistical machine learning techniques for problems in genomics.
