While machine learning methods have traditionally been used for prediction in fields like industry and technology, they are increasingly being adopted in scientific research for exploration and inference. This two-part workshop introduces key machine learning techniques used for scientific applications. Part 1 discusses core concepts such as prediction accuracy, the bias-variance tradeoff, and cross-validation. Part...
While machine learning methods have traditionally been used for prediction in fields like industry and technology, they are increasingly being adopted in scientific research for exploration and inference. This two-part workshop introduces key machine learning techniques used for scientific applications. Part 1 discusses core concepts such as prediction accuracy, the bias-variance tradeoff, and cross-validation. Part 2...
Machine learning is playing an increasingly important role in science and technology. In this advanced session, we focus on leveraging scikit-learn for high-performance machine learning. We will explore how to speed up model training using multicore processors and accelerators, as well as techniques for out-of-core learning. This workshop builds on the foundational concepts from the...