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Workshop: Lessons from Binary Classification

May 12, 2017 @ 12:00 pm - 2:00 pm

Instructor: James Sharpnack

Date: May 12, 2017

Time: 12:00pm

Description:

Binary classification is the canonical machine learning task and its study
has a rich history. Much of the main principles of machine learning have
been discovered in this context. These principles continue to guide the
broader development of machine learning, and they motivate methods such as
cross-validation, kernel support vector machines, logistic regression, and
neural networks. We will highlight the resultant methods and will
accompany this with data driven examples.

Prerequisites:

Bring a laptop pre-loaded with Jupyter, Python, NumPy and
Scikit-Learn (they can be installed through [Anaconda].

Resources:

video 1

video 2

Details

Date:
May 12, 2017
Time:
12:00 pm - 2:00 pm

Organizer

DataLab: Data Science and Informatics (DSI)
Website:
https://datalab.ucdavis.edu

Venue

Shields Library, room 360