Python Programming and Machine Learning 2

Learn inter­me­di­ate Python pro­gram­ming and how to pro­gram a machine learn­ing (ML) appli­ca­tion. The class will imple­ment a bina­ry Naïve Bayes clas­si­fi­er from scratch, over the course. Impor­tant ML con­cepts such as super­vised learn­ing, qual­i­ty train­ing data, cross val­i­da­tion, pre­ci­sion, recall, and a con­fu­sion matrix will be dis­cussed and imple­ment­ed in Python. Includes hands-on, in-class exer­cis­es, stu­dents must be pre­pared to (in class) write Python pro­grams, indi­vid­u­al­ly or in a group. Pre­req­ui­site: EXSC 2500
Course at a glance

Update (Oct 7) - The prerequisite is waived for this class, please call 780-492-3116 to register. If you have completed EXSC 2500, enrollment may be completed online.

Currently counts towards

* If you are already enroled in this program, please refer to your specific program requirements as outlined at the time of your admission: Bear Tracks > Academic Advisement.

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We recommend that you apply to the program as soon as possible to lock in your course requirements as they are subject to change.

This is a skills-enhancing course in
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