Introduction to Energy Machine Learning
The objective of this training event is to learn the theory and practical application of machine learning within the Energy industry to help improve data-driven decision making.
A brief description of the training follows:
Introduction
- Introduce topics and overview of Subsurface Machine Learning.
Introduction to Machine Learning
- Provide definitions, fundamental concepts of inference and prediction along with the opportunity and limitations of machine learning.
Inference
- Learn about the system with limited observations. Sampling bias, Feature Selection, and more.
Prediction
- Motivation and methods for predictive machine learning methods including hyper parameter tuning with k nearest neighbors.
Machine Learning Examples
- Real world applications of Subsurface Machine Learning.
Location:
Online - No recording - Interactive learning: A link to daytum Learning Management System will be provided to the registrants before the training.