8.1 Technical requirements
All of the code for this book can be found on the GitHub repository for the book: https://github.com/PacktPublishing/Enhancing-Deep-Learning-with-Bayesian-Inference.
Matt Benatan is a Principal Research Scientist at Sonos and a Simon Industrial Fellow at the University of Manchester. His work involves research in robust multimodal machine learning, uncertainty estimation, Bayesian optimization, and scalable Bayesian inference.
Read more about Matt Benatan
Jochem Gietema is an Applied Scientist at Onfido in London where he has developed and deployed several patented solutions related to anomaly detection, computer vision, and interactive data visualisation.
Read more about Jochem Gietema
Marian Schneider is an applied scientist in machine learning. His work involves developing and deploying applications in computer vision, ranging from brain image segmentation and uncertainty estimation to smarter image capture on mobile devices.
Read more about Marian Schneider
All of the code for this book can be found on the GitHub repository for the book: https://github.com/PacktPublishing/Enhancing-Deep-Learning-with-Bayesian-Inference.
Matt Benatan is a Principal Research Scientist at Sonos and a Simon Industrial Fellow at the University of Manchester. His work involves research in robust multimodal machine learning, uncertainty estimation, Bayesian optimization, and scalable Bayesian inference.
Read more about Matt Benatan
Jochem Gietema is an Applied Scientist at Onfido in London where he has developed and deployed several patented solutions related to anomaly detection, computer vision, and interactive data visualisation.
Read more about Jochem Gietema
Marian Schneider is an applied scientist in machine learning. His work involves developing and deploying applications in computer vision, ranging from brain image segmentation and uncertainty estimation to smarter image capture on mobile devices.
Read more about Marian Schneider