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DESCRIPTION:Machine Learning in Python - Neural networks part 2 & AI Ethics
 \n\nOverview: In this lesson\, we will redo the example of recognizing han
 dwritten digits\, but this time using a different kind of neural network m
 ore suited to image recognition tasks – convolutional neural networks. We 
 will mention a few other forms of neural networks and their typical use ca
 ses. Finally\, since neural networks are extraordinary tools\, we will dis
 cuss the responsibility that we as ML practitioners have to use them ethic
 ally. We will look at situations where AI falls short of its promises\, so
 metimes in spectacularly funny ways\, and other times in devastatingly sad
  ways.\n\nLearning Goal(s): By the end of the workshop\, participants will
  be able to:\n\n\n	Critique the use of AI in a social context.\n	Enumerate t
 he different kinds of neural networks together with their associated use c
 ases.\n	Given a scaffolded environment and curated data set\, follow a tuto
 rial that trains a convolutional neural network to perform classification.
 \n\n\nPrereqs: Participants should already have some familiarity with Pyth
 on programming fundamentals\, e.g. loops\, conditional execution\, importi
 ng modules\, and calling functions. Furthermore\, participants should idea
 lly have attended the first lesson in the “Fundamentals of Machine Learnin
 g in Python” series\, or they should already have some background on the g
 eneral machine learning pipeline.\n\nApproach: Our approach is primarily s
 tudent-centered. Students will work in pairs and small groups on worksheet
 s and Jupyter notebooks\, interspersed with brief lecture and instructor-l
 ed live-coding segments.\n\nSupporting Resources: We will refer to many of
  the materials used previously in our series “Computing Workshop” https://
 computing-workshop.com/\n\nDeliverables: Our resources will be made availa
 ble via our web site.\n\nResources required: Participants should have acce
 ss to a laptop computer. Python should be already installed with Anaconda.
 \n\nLocation: HYBRID. McIntyre Medical Building\, room 325\, and via Zoom.
 \n	Instructor: Jacob Errington\, Faculty Lecturer in Computer Science at Mc
 Gill University. Eric Mayhew\, Computer Science professor at Dawson Colleg
 e.\n\nRegistration: Register Here\n
DTSTART:20241128T150000Z
DTEND:20241128T170000Z
SUMMARY:Workshop: Machine Learning in Python - Session 5
URL:/cdsi/channels/event/workshop-machine-learning-pyt
 hon-session-5-360405
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