Matt Benatan - ebooki

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.

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Tytuły autora: Matt Benatan dostępne w księgarni Helion

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
Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python

Matt Benatan, Jochem Gietema, Marian Schneider

159.00 zł

Matt Benatan - ebooki

Tytuły autora: Matt Benatan dostępne w księgarni Helion

Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python

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Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python