Dr. Matt Benatan is a research scientist in Machine Learning and AI in Sonos's Context Awareness research group. I have significant expertise in developing and applying Machine Learning techniques across a variety of domains, including Audio DSP, Speech Processing, and Computer Vision. I have also worked extensively on the development and application of Bayesian methods, including Bayesian optimisation and scalable Bayesian inference (with a focus on Bayesian neural networks). Collaborator and PhD co-supervisor on a couple of research projects with the University of Manchester.
Graduate of the University of Leeds with a PhD in Audio-Visual Speech Processing (Computer Science), Master's degree in Computer Science and Electronics (MSc by Research) and a BSc (Hons) degree in Music, Multimedia and Electronics.
Matt Benatan
Tytuły autora: Matt Benatan dostępne w księgarni Ebookpoint
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This book provides a comprehensive introduction to Bayesian deep learning methods for machine learning researchers and practitioners. It discusses the importance of uncertainty in machine learning, covers numerous methods for uncertainty-aware deep networks, and provides detailed code examples in Python to assist you throughout your exploration.-
- PDF + ePub 134 pkt
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