comp 551 applied machine learning - sarath...
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COMP 551 Applied Machine Learning
Instructor: Sarath Chandar
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Applied Machine Learning Sarath Chandar
Instructor
Sarath Chandar
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Applied Machine Learning Sarath Chandar
Lead Teaching Assistant
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Prasanna Parthasarathi
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Applied Machine Learning Sarath Chandar
Teaching Assistants
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Ali Emami Scott Fujimoto Carlos Gonzalez Gandharv Patil
Edward Smith Xin Tong Wang Nadeem Ward
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Applied Machine Learning Sarath Chandar
Course Details
Website: http://sarathchandar.in/teaching/2018/fall/comp551/
Schedule: http://sarathchandar.in/teaching/2018/fall/comp551/schedule.html
Schedule will be updated regularly! So it is always tentative!
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Applied Machine Learning Sarath Chandar
What is this course about?
This is an introductory course in Machine Learning which covers fundamental topics in supervised learning and unsupervised learning.
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Applied Machine Learning Sarath Chandar
Course Structure
● 2 lectures per week.● Weekly reading.● In-class surprise quizzes.● 1 in-class end-term exam.
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● 3 tutorial sessions in total.● 3 programming assignments.● 1 Kaggle competition.● 1 final project.
Theory Practice
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Applied Machine Learning Sarath Chandar
Grading Info
● In-class surprise quizzes - 10%● 3 programming assignments (individual) - 25%● Kaggle competition (team of 3*) - 15%● Course Project (team of 3*) - 20%● Written Exam - 30%
● You cannot have same team members for both competition and project.
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Applied Machine Learning Sarath Chandar
Programming Assignments
● 3 programming assignments.● Individual assignments.● Submission instructions will be released with the assignments.● Late work will be subject to a 30% penalty, and can be submitted up to 3 days after the
deadline.● We will use gradescope for all the course related submissions.● You have to use Python 3 for all the three assignments.● Tutorial-1 will cover introduction to python 3.
○ Date: September 14○ Time: 6 pm to 7:30 pm○ Venue: ENGMC 304
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Applied Machine Learning Sarath Chandar
Code of Conduct
● Zero tolerance for plagiarism and cheating!● Each assignment/project/competition comes with rules and you MUST follow them.
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Applied Machine Learning Sarath Chandar
Prerequisites
● Knowledge of a programming language.● Knowledge of probabilities/statistics (e.g. MATH-323, ECSE-305).● Knowledge of calculus and linear algebra.● Some AI background is recommended (e.g. COMP-424, ECSE-526) but not required.● First week’s reading covers some prerequisite materials.
● Assignment-0 covers some problems based on the prerequisites. This is NOT graded. But you must submit them to get used to Gradescope.
● Assignment-0 is already out!
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Applied Machine Learning Sarath Chandar
Discussions
● We will use reddit for class discussions.● Check myCourses for link to the subreddit for the class.● You can post your questions lecture-wise.● Please do not create a new link or a post. Use the posts assigned for corresponding
lecture.● Sign up before next class!● If you are not in myCourses, email Prasanna with your first name, last name,
McGill ID, and your reddit user name.
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Applied Machine Learning Sarath Chandar
Course Feedback
● You can submit your feedback about the course at any point of time.● Check myCourses for a link to the Google form. (Also available in Reddit)● Feel free to give both positive and negative feedback about every lecture!
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Applied Machine Learning Sarath Chandar
Surprise Quizzes
● Any number of surprize quizzes.● Always bring an A4 sheet and pen to the lectures.
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Applied Machine Learning Sarath Chandar
Course calendar
● Course calendar available in the website.● Check the calendar for
○ Office hours location and time.○ Tutorials location and time.○ Submission deadlines.
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Applied Machine Learning Sarath Chandar
Email Policy
● All your emails about sick leave, extensions, complaints should be directed to Prasanna only. Email me only if it is very personal.
● Do NOT email the TAs for course doubts or assignment doubts. You doubts should be posted only in Reddit forum.
● Do NOT email the TAs for regrading your assignments. Assignment regrading will be done only through Gradescope.
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Applied Machine Learning Sarath Chandar
Tips to excel in the course..
● Read the lecture notes of the previous class before coming to the class.● Finish all the readings that are assigned every week.● Do all the self-assessment questions posted for every lecture.● Attempt to solve all the non-graded assignments too.
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