Forecasting Team Meeting - October 11, 2016
Attended: Dr.Kuh, Brieanna, Jaimie, Gordon
Updates
- Proposal for presentation:
- Understanding data
- Mean vectors
- Covariance matrices
- Representation of data
- Sampling/filtering
- Machine learning algorithms
- Feature extraction
- Clustering
- Principle component analysis (PCA)
- Linear regression
- Least squares' algorithm
- Online learning
- Recursive least squares (RLS)
- Least mean squares (LMS)
- Tools for learning
- Validation
- Regularization
- Getting working, documented code in Python
- Calibration of data
- Interface data to UHM dashboard
- Introduction to tap filters and correlation matrices
Problems
- none
Reminders
- none
Authors
Contributing authors:
Created by jobatake on 2016/11/30 04:08.