Introduction to basic concepts of machine learning and statistical pattern recognition; techniques for classification, clustering and data representation and their theoretical analysis.

Prerequisites: 3521, 5521, or 5243; and 5522, Stat 3460, or 3470; and Math 2568, 2174, 4568, or 5520H; or Grad standing.

Textbook (optional):

1. Christopher M Bishop, Pattern recognition and machine learning. Springer, 2006.

2. Kevin P. Murphy, Machine Learning: A Probabilistic Perspective. The MIT press, 2012.

3. Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep learning. The MIT press, 2016.

Useful resource: Kaare Brandt Petersen and Michael Syskind Pedersen, The Matrix Cookbook

• (45%) Homework

  1. There will be 6 homework assignments (lowest dropped). We will have coding questions so make sure you are familiar with at least one programming language.

  2. Each student should complete homework independently. You are allowed to discuss with others but you need to list their names.

  3. Homework should be neat and recognizable, you are encouraged to type your answers in LaTex.

  4. Late homework policy: homework will be accepted up to three days late with a penalty of 20% per day

  5. Regrade requests: you may request for a regrade by turning to TA a sheet of paper with your name, osu email, which homework problem you want to be regraded, how many points you think you deserve, and the reason why you think you deserve those points. The requests should be submitted within one week after the grades are released.

• (25%) Midterm Exam

• (25%) Final Exam

• (5%) Participation

  1. Questions related to this course should be asked in Piazza, students are encouraged to answer each other's questions and have group discussions.

• Announcements will be made through Carmen website.

• Slides, recourses, homework will be posted on Carmen.

• We will use Piazza for discussion or questions.

  1. Sign up: piazza.com/osu/spring2022/cse5523

  2. Any questions related to course materials or policy should ask in Piazza.

  3. Email TA only if it’s too personal for Piazza

  4. Email me if it’s too personal for TA Tag “[CSE-5523]” in subject line

• To maintain the health and safety of our campus, each student should follow the university guideline:

  1. Masking remains mandatory in the classroom. Masks must cover your nose, mouth, and chin (check out the masking rule)

  2. Remember to keep social distance in the classroom.

  3. Given the significant increase in transmissibility of the omicron variant, nobody should eat or drink in classrooms.

  4. If you are sick, please send me an email immediately and fill out an accommodation form with Student Life Disability Services (SLDS)