Educational Lecture Series on Quantitative Microscopy & Image Analysis
All lectures will be held in Warren Alpert Room 563 from 12pm-1pm.
They are open to anyone with a Harvard or Harvard affiliate ID (and guests of those with Harvard IDs), and registration is not required.
Note, if you forward this email to someone outside of Harvard, please also make plans to escort them through security!
March 3rd
Seeing the Random Forest for the Trees: Machine Learning in Bio-Image Analysis
Dave Richmond, PhD (IDAC)
Machine learning is one of the pillars of modern image and data analysis, and is finding new applications every day in our data driven world. This lecture will give a first introduction to machine learning through a simple yet powerful technique: Random Forests. Random Forests are behind one of the biggest commercial successes of computer vision (Microsoft Kinect), and have widespread use in medical and bio image analysis. In fact, if you've used FIJI's Trainable Weka Segmentation, or the ilastik program, then you've already worked with one.
Level: Beginner to intermediate. We will do our very best to avoid any equations, and will focus on conceptual understanding. You will learn what a Random Forest is, how it works, and how to tune its parameters. You don't need to know statistics or optimization theory, but it will help if you've played 20 questions before.
LOCATION:Warren Alpert Room 563 HMS campus STATUS:CONFIRMED DTSTART:20160303T170000Z DTEND:20160303T180000Z END:VEVENT END:VCALENDAR