Deep Learning with Yacine on MSN

Adadelta optimizer explained – Python tutorial for beginners & pros

Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...
Deep Learning with Yacine on MSN

Nadam optimizer explained: Python tutorial for beginners & pros

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...
Scientific Research Publishing

Heckerman, D. (1995) A Tutorial on Learning with Bayesian Networks. Microsoft Research Technical Report.

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
Law

Bayesian One Year On: The Superyacht Disaster That Has Sparked Multiple Lawsuits

A year ago today, a violent storm struck the coast of the sleepy Sicilian fishing village of Porticello. High winds and dramatic thunder and lightning are not unheard of around this time of year in ...
iaea.org

New IAEA Video Tutorials on Computed Tomography for Medical Physicists

Olivera Ciraj Bjelac, IAEA Department of Nuclear Sciences and Applications To support hospitals and specialists around the world in meeting their safety standards requirements, the IAEA has produced a ...
CNN

First major piece of Bayesian superyacht recovered from seabed

Salvage crews have recovered the boom from the $40 million Bayesian luxury yacht, which sank off the coast of Sicily in August 2024, killing seven people, including British tech tycoon Mike Lynch and ...
CNN

Inside the Bayesian’s final moments: extreme winds sank superyacht, interim report finds

Sudden, hurricane-force winds toppled the luxury Bayesian superyacht that sank off the coast of Sicily last August, according to an interim report into the disaster, which found the boat had ...
C&EN

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...
Scientific Research Publishing

Sivia, D. and Skilling, J. (2006) Data Analysis: A Bayesian Tutorial. OUP Oxford.

ABSTRACT: Soil-water characteristic curve (SWCC) is significant to estimate the site-specific unsaturated soil properties (such as unsaturated shear strength and coefficient of permeability) for ...
Time

AI-powered Bedsore Prevention

These are independent reviews of the products mentioned, but TIME receives a commission when purchases are made through affiliate links at no additional cost to the purchaser. Some 2.5 million people ...
marktechpost

Embed-then-Regress: A Versatile Machine Learning Approach for Bayesian Optimization Using String-Based In-Context Regression

Bayesian Optimization, widely used in experimental design and black-box optimization, traditionally relies on regression models for predicting the performance of solutions within fixed search spaces.