About this course
This course provides an introduction to machine learning and data mining. Topics include:
- Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels).
- Unsupervised learning (clustering, dimensionality reduction, recommender systems).
- Best practices in machine learning (bias/variance theory).
The course will applicable to numerous case studies - text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
Whom this course is for
Students of "Digital Technologies, Networks and Big Data" master's program, Institute of Information Technology and Data Science, INRTU