Syllabus
The seminar provides an experience in data analysis. It extends the lecture Introduction to Machine Learning.
Lectures introduce to machine learning tools and library functions usage. Participants of the seminar analyze a given dataset and submit their results as a seminar work.
The lectures cover:
- graphs (scatter plot, box plot and basic graphs and graph annotations)
- groupby function and group statistics
- simple classification and regression models
- evaluation with respect to different error functions
- ways to identify outliers, missing data handling.
According a specific dataset we may further focus at:
- time series,
- text tfidf vectorization,
- clustering and apriori algorithm.
Annotation
Lectures introduce to machine learning tools and library functions usage. Participants of the seminar analyze a given data set and submit their results as a seminar work.