Each .ipynb file is provided by a corresponding .html file or a link to Google Colaboratory or Kaggle.
- EPAM_projects contains homeworks from EPAM Data Science introduction course (2021).
- EPAM_NLP_advanced contains projects from EPAM NLP advanced mentor program (dec 2021 - feb 2022).
- Kaggle contains notebooks from Kaglle (obviously) which are also available here
- Concrete_regression - my exam work for "Applied machine learning" course. The goal: to predict the strength of concrete by its characteristics. (2021)
- Perceptron - implementation of the exercise from the book "Python Machine Learning" by S. Rashka and V. Mirjalili.
- clusreting_kmeans - my laboratory work for "intellectual data analysis" course. The goal contains two parts: to provide self-made implementation of kmeans clustering algorithm and to analyse dataset "USA cities" using various cluster algorithms.
- news_group_classification - my work for "Applied machine learning" course. The goal: to classify news by topic.
- students_notes - contains two projects: Exploratory Data Analysis and supervised learning on the same dataset, which contains information about students from different schools and their notes.