Data Science 561:

Predictive Analytics (4.0 units)

Supervised learning. Linear regression, cross validation, ridge and lasso regression, logistic regression, k-nearest-neighbors, decision trees, random forest and gradient-boosting models, support vector machines, neural networks.
  • Crosslist: This course is offered by the ISE department but may qualify for major credit in DSCI. To register, enroll in ISE 529.
SectionSessionTypeTimeDaysRegisteredInstructorLocationSyllabusInfo
31529D048Lecture2:00-3:50pmMon, Wed42 of 45Maryam PishgarOHE122session dates
31546D048Lecture2:00-3:50pmMon, Wed71 of 75Cesar Acosta-MejiaZHS352PDF (305920 KB)session dates
31726D048Lecture5:00-6:50pmMon, Wed46 of 90Cesar Acosta-MejiaSLH100PDF (306053 KB)session dates
31729D048Lecture12:00-1:50pmMon, Wed30 of 40Maryam PishgarDMC211session dates
31731D034Lecture2:00-3:50pmMon, Wed8 of 20Maryam PishgarDEN@Viterbisession dates
Information accurate as of January 19, 2024 5:02 pm.