📗 -> Neural networks and machine learning in biology
short mode
not done
tags include #BML
description includes foo🔗 Critical Links
- Put important links for class
🔶 Course Description
This course provides an introduction to the exciting frontier between biology and machine learning. There are two themes to this course.
- The first theme focuses on neural network models, which are both powerful tools for understanding information processing in the brain and underlie many of the striking recent successes of machine learning. We will introduce and contrast canonical examples of neural networks and learning rules in neuroscience and machine learning, and discuss how ideas about brains and computers have historically influenced and continue to influence each other.
- The second theme explores the use of machine learning/AI in biological research and health, and the accompanying policy and ethical considerations. The focus here will be on helping you explore a topic of interest and sharing it with the class.
❗ Important
Instructor:
- Rishidev Chaudhuri - rchaudhuri@ucdavis.edu
📄 Class Material
Week 1 - Course Intro
Week 2 - Perceptrons, Learning
Week 3 - Supervised Learning, Cerebellum
Week 4 - Multilayer Networks, Images
Week 5 - Visual System, Modeling Sensory Cortices
Week 6 - Recurrent Nets, Memory
Midterm