DSCI 631 Applied Machine Learning for Data Science 3.0 Credits
Introduces relevant topics in the life cycle of machine learning: extracting and engineering features, tuning parameters, comparing algorithms, interpreting results, and analyzing errors. Students will be exposed to various representative algorithms in the concept level and learn their trade-offs. Students will gain hands-on experiences with assignments and a term project. Students will be prepared to attack new problems using various machine learning methods and be able to compare the performance of different algorithms for the term project.
Repeat Status: Not repeatable for credit
Prerequisites: DSCI 521 [Min Grade: C] (Can be taken Concurrently)