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INFO-4604, Applied Machine Learning University of Colorado Boulder August 29, 2017 Prof. Michael Paul Information Public website Lecture slides, readings, policies http://cmci.colorado.edu/classes/INFO-4604/ Piazza

  1. INFO-4604, Applied Machine Learning University of Colorado Boulder August 29, 2017 Prof. Michael Paul

  2. Information • Public website • Lecture slides, readings, policies • http://cmci.colorado.edu/classes/INFO-4604/ • Piazza • Discussion, assignments • http://piazza.com/colorado/fall2017/info4604 • D2L • Grades • http://learn.colorado.edu

  3. What is machine learning? Murphy: • “a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data” Essentially: learning from data (Learning to do what? We’ll see examples.)

  4. What makes this applied? Compared to other courses… • More emphasize on using existing tools than implementing algorithms • But you’ll do a little bit of implementation too • Less mathematical theory • But you’ll still learn how the algorithms work • Math will be taught as needed • More focus on creating systems/pipelines (data processing, design, evaluation)

  5. Goals After this course, you should be able to: • identify when machine learning can help solve a problem and which approaches are appropriate; • be comfortable doing machine learning in Python, and be familiar enough with the algorithms and parameters to easily adopt other toolkits; • understand the underlying concepts well enough that you can read machine learning papers, and can modify implementations for your own needs.

  6. Background Programming background: Python Where to go for help? • Ask questions on Piazza with ‘python’ tag • Asking (not just answering) questions on Piazza helps your participation grade! • Look at examples that come with the book; experiment with editing the code so that you understand it better

  7. Background Math background: nothing specifically assumed • prior exposure to discrete math, probability, and basic linear algebra would be helpful Where to go for help? • Ask questions on Piazza with ‘concepts’ tag • Asking (not just answering) questions on Piazza helps your participation grade! • Review the free OpenIntro Statistics textbook

  8. 4604 vs 5604 Graduate students should be enrolled in 5604 5604 students will have to do additional problems on homework/quizzes/exams, and are assigned additional readings • 4604 students can do the 5604 problems for extra credit

  9. Attendance I may give unannounced quizzes if low attendance becomes a problem. If you need to miss a class, let me know before the lecture. If you are affected by Hurricane Harvey, we can discuss accommodations.

  10. Laptop Policy I don’t think we’ll do anything in class that requires a laptop (but I’ll let you know if there are days where it would help) If you use a laptop in class, please be respectful of your neighbors (nothing distracting on your screen)

  11. Homework I will assign and grade the first programming assignment before the drop deadline (Wed, Sept 13).

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