Machine learning is the systematic study of algorithms and systems that improve their knowledge and performance with experience. Collecting and analyzing data through machine learning algorithms and models can uncover complex patterns in massive amounts to data to make more accurate predictions and to reveal coherent dimensions. In this course students will consider classification, regression, clustering, subgroup, and association models to predict and describe, using supervised and unsupervised learning methods. Special attention will be given to models and techniques that aid and support the visualization of complex data.

Machine learning is the systematic study of algorithms and systems that improve their knowledge and performance with experience. Collecting and analyzing data through machine learning algorithms and models can uncover complex patterns in massive amounts to data to make more accurate predictions and to reveal coherent dimensions. In this course students will consider classification, regression, clustering, subgroup, and association models to predict and describe, using supervised and unsupervised learning methods. Special attention will be given to models and techniques that aid and support the visualization of complex data.

Machine learning is the systematic study of algorithms and systems that improve their knowledge and performance with experience. Collecting and analyzing data through machine learning algorithms and models can uncover complex patterns in massive amounts to data to make more accurate predictions and to reveal coherent dimensions. In this course students will consider classification, regression, clustering, subgroup, and association models to predict and describe, using supervised and unsupervised learning methods. Special attention will be given to models and techniques that aid and support the visualization of complex data.