IT 556 MACHINE LEARNING

Students will obtain the ability to build both supervised and unsupervised machine learning models. In constructing such models, students shall develop a variety of 'art and practice' skills such as: use of Git and GitHub; use of Jupyter notebooks, and how to leverage multiprocessing with multiple cores on their own computer. Students will also enhance existing skills learned in IT540 including data acquisition, data cleaning, data imputation, data exploration and visualization, hyperparameter estimation, cross validation, modeling and others. These skills will be developed through text readings, significant 'hands-on' execution of provided Jupyter notebooks using the Python language, and development of end-to-end modeling projects. Additional readings and videos may be assigned by the instructor.

Credits

Prerequisite

IT 533 and IT 545

Distribution

INFORMATION TECHNOLOGY