Introduction to machine learning concepts in analytics; data preprocessing and visualization; quality metrics in machine learning; construction, applications and validation of regression, decision tree, random forest, ensemble and text analytics; internet programming using Python. Credits 1 to 4. 1 to 4 Lecture Hours.
Introduction to machine learning concepts in analytics; data preprocessing and visualization; quality metrics in machine learning; construction, applications and validation of regression, decision tree, random forest, ensemble and text analytics; internet programming using Python. Credits 1 to 4. 1 to 4 Lecture Hours.
