Machine learning in Economics and Finance
- Know the basic problem statements, models and methods of machine learning.
- Able to apply algorithms for estimating model parameters and building forecasts.
- Have skills in identifying machine learning methods appropriate for the research objective.
- Have skills in identifying statistical outliers and filling in missing values.
- Able to formulate a statement of the problem according to the proposed data. Selects a suitable forecast model for the existing task. Knows basic tests for comparing model quality. Able to use tests to select the most suitable model for the task.
- Able to formulate the statement of the problem of teaching without a teacher according to the proposed data. Selects the appropriate teaching method for the existing task. Knows basic tests for selecting adequate methods and searching for hyperparameters.
- HomeworkWritten report in electronic format assigned by the teacher completed in paris or alone. It should be finished and loaded to LMS before the deadline.
- Online courseTaking online courses, preparing its notes and confirming studying the material by passing the test, answering questions or preparing presentaton.
- ExamWritten report in electronic format completed in pairs or alone. It should be finished and loaded to LMS before the deadline given by the teacher. Report includes answers to the list of questions provided to students no later than two weeks before exam.
- Mohammed, Mohssen Khan, Muhammad Badruddin Bashier, Eihab Bashier Mohammed. Machine Learning: Algorithms and Applications. Auerbach Publications © 2017 // https://library.books24x7.com/toc.aspx?bookid=117434
- Trevor Hastie, Robert Tibshirani , et al., The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd edition, 2017. Free from the publisher: https://web.stanford.edu/~hastie/ElemStatLearn/printings/ESLII_print12.pdf
- Lantz, B. (2013). Machine Learning with R : Learn How to Use R to Apply Powerful Machine Learning Methods and Gain an Insight Into Real-world Applications. Birmingham, UK: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=656222
- Matt Taddy. (2019). Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions. McGraw Hill.