Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods and Summary of Course

 

 

 

Scientific Machine Learning

An important and emerging field is what has been dubbed as scientific ML, see the article by Deiana et al Applications and Techniques for Fast Machine Learning in Science, arXiv:2110.13041

The authors discuss applications and techniques for fast machine learning (ML) in science – the concept of integrating power ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The report covers three main areas

  1. applications for fast ML across a number of scientific domains;
  2. techniques for training and implementing performant and resource-efficient ML algorithms;
  3. and computing architectures, platforms, and technologies for deploying these algorithms.