Prerequisites and co-requisites: Basic knowledge of Python programming language is expected. It is recommended to complete Programmer in 4 days course / Basic data modeling and advanced statistical testing course.
Course Information: Types of machine learning: learning with a teacher, without a teacher, empowering. Difference between classification and regression. Explanation of training and its unwanted aspects – overestimating and underestimating. Basic acquaintance with the most used training models of machine learning.
Tutorial on working with Python tools used in machine learning: NumPy for working with fields, Pandas for table data processing and Matplotlib for graphing. Solution of practical tasks in the scikit-learn library from data preparation to evaluation of the tested model and visualization of results.
Acquired knowledge: Ability to be oriented in machine learning methods and select a suitable model for given data. Evaluation of the ability to predict a trained model and its visualization. Optimizing the selected model by pre-processing data and selecting appropriate parameters.
Course duration: 2-3 days
