CSE 450 Syllabus
Course Information
Course: CSE 450 - An Introduction to Machine Learning & Data Mining
Prerequisites: CS 241 or CS 246
Text: Marsland, Machine Learning, An Algorithmic Approach, 2nd Edition
The textbook is also available online through our library subscription.
During the second half of the semester, we will also refer to a few chapters from the e-book, Machine Learning with R
Objectives/Outcomes
My hope is that at the end of this course each student will:
Be excited about machine learning and data mining
Have the ability to tackle a real dataset and do something interesting with it
Be prepared to start a graduate level experience, class, or project in machine learning / data mining
Understand current challenges and limitations in the field.
Content
To achieve these outcomes, we will have assignments and assessments in the following areas:
Readiness Assurance Tests
There will be assigned reading material each week from the textbook and other online sources. Each student is expected to come to class Monday prepared and will be given a short readiness assurance test individually and as a group to verify this.
Activities
Most weeks will include an activity where students practice the concepts of the week prior to applying them in their larger project of the week.
Assignments/Projects
Each week, there will be an individual assignment that reinforces the concepts discussed. Some of these will be Python programs, others will be experimentation and analysis using existing tools.
Semester Project
Students will spend the majority of the second half of the semester working on a Semester project. For this project, each students will select and obtain a dataset of their choosing and mine it to discover new and interesting insights.
Exams
There will be a comprehensive final exam at the end of the semester.
GRADING POLICY
Grades will be assigned according to the following breakdown:
Readiness Assurance Tests: 10%
Activities: 10%
Assignments/Projects: 40%
Semester Project: 30%
Exams: 10%
Assessments
Grades for most assignments (unless otherwise noted) are assigned in broad terms according to the following scale:
50% - Some attempt was made
70% - Developing, but significantly deficient
85% - Slightly deficient, but still mostly adequate
93% - Meets requirements
100% - Shows creativity, and a desire to excel above and beyond
Final Grade Scale
| A | 93-100 |
| A- | 90-92 |
| B+ | 87-89 |
| B | 83-86 |
| B- | 80-82 |
| C+ | 77-79 |
| C | 73-76 |
| C- | 70-72 |
| D+ | 67-69 |
| D | 63-66 |
| D- | 60-62 |
| F | 0-59 |
Honor Code
Academic Honesty
You are expected to follow the university's policies for academic honesty.
You may work with your classmates but all submitted work for projects and assignments must be original. Share ideas; do not share code! Assistance from a classmate should be on par with the help you would expect from a lab assistant.
If you work closely with another student, helping teach and learn from each other, make sure you each still write your own code, but in this case, your solutions may end up being very similar. This is completely fine, but please make sure to put a comment in your code stating that you wrote your own program, but worked closely with that person, and that is why it is similar.
You are encouraged to use the Internet as a resource, but recognize that you should not copy and paste someone else’s work as your own. Cite all sources and follow copyright laws. When in doubt, give credit and be upfront.
Do not look for or share solutions on "note sharing" internet sites.
The penalty for copying or plagiarism of assignments might be one or more of the following: -100% on an assignment, being asked to withdraw from the class, a failing grade in the class, or disciplinary action by the University.
Dress and Grooming
You are expected to follow the university's Dress and Grooming Standards
Grievance Policy
Review the Academic Student Grievance Policy.
Student Support
Support is available in many ways including via other class members and discussion in Slack. In addition, help is available through the university's academic support center.
Sexual Harassment
BYU-Idaho is committed to promoting and maintaining a safe and respectful environment for the campus community. Sexual misconduct is against the law, contrary to the teachings of The Church of Jesus Christ of Latter-day Saints and the Honor Code and inconsistent with the life and teachings of Jesus Christ, which we hope are embodied on our campus. The university prohibits sexual misconduct perpetrated by or against university students, university employees, participants in university programs, or visitors to its campus, whether the behavior occurs on or off campus.
Click here for more information.
Students with Disabilities
Brigham Young University-Idaho is committed to providing a working and learning atmosphere that accommodates qualified persons with disabilities. If you have a disability and require accommodations, please contact the Disability Services Office (208) 496-9210. Reasonable academic accommodations are reviewed for all students who have qualified documented disabilities. Services are coordinated with the students and instructor by the Disability Services Office.
Changes to Schedule and Assignments
Schedules, assignments, and policies are subject to change. You will be notified of any changes on I-learn.