BICF Machine Learning 1 - Nanocourse
Have you heard about machine learning and feel it may be of some value for your research? This nanocourse will introduce machine learning from the ground up. No prior experience in machine learning is necessary.
Topics for this two day (all-day) course will include:
- Intro to machine learning
- Supervised learning including:
- Regularization to handle overfitting
- Intro to neural networks
- Intro to convolutional neural networks for image analysis
- Unsupervised learning including
- dimensionality reduction
- Probabilistic graphical models (PGM)
- fundamentals of the PGM formalism
- representation with PGMs
- learning model parameters
- inference from the model
The course will be interactive, with lectures followed by hands-on learning and exercises. Familiarity with basic programming/scripting concepts is assumed as is some prior programming experience in python.
You will not need to bring a laptop computer for this course. When you arrive you will loginto a prepared account on the BioHPC.
Course Administration: Rebekah Craig
Preparation for Class
- You only need to arrive on time.
- The training accounts will be setup apprpriately for the interactive exercises.
- If you with you may review how to use Jupyter notebooks, as these will be primarily used for the hands on portions of the course.
Day 1 | March 8th, 2018
Day 2 | March 9th, 2018
TAs: Andrew Jamieson, Behrouz Saghafi Khadem, Bo Ci, Devin O'Kelly, Jeon Lee, Minzhe Zhang, Viren Amin, Yi Du