stepikods

• Here there my notebooks with ODS and Stepik courses
• ODS course is similar to https://mlcourse.ai/
• Stepik course is here https://stepik.org/course/4852/syllabus

Topics:

1. Pandas
2. Visualization with Matplotlib, Seaborn, Plotly
3. Decision Trees (GridSearchCV), kNN, cross-validation (K-fold)
4. Linear Classification and Regression
5. Bootstrap, Bagging and Random Forest
6. Feature Engineering and Feature Selection
7. PCA and Clustering (K-means, Affinity Propagation, Agglomerative clustering, DBSCAN)
8. SGD, Online learning, Vowpal Wabbit
9. Time series analysis (smoothing, Time series cross validation, Stationarity, basics of ARIMA
10. Gradient Boosting

Libraries:

• Pandas
• Matplotlib, Seaborn, Plotly
• Scikit-learn
• Vowpal Wabbit
• Statsmodels
• Facebook Prophet
• XGBoost, LightGBM, Catboost

Also I included my trainings dedicated to algorithms and data structures This is a test message