| Laboratory # | Topic |
|---|---|
| Lab #1 | Loading data, splitting data into training and testing sets, Decision Tree Classifier |
| Lab #2 | Pipelines, Scallers, SVM, metrics: accuracy, confusion matrix, mse; LinearRegression, DecisionTreeRegression |
| Lab #3 | Scallers, data visualization, DecisionTreeClassifier, pandas, DecisionBoundaryDisplay |
| Lab #4 | Imputting missing data, Removing outliers, Creating ProfileReport, Cross validation, RandomizedSearchCV, Voting Classifier, Stacking Classifier |
| Lab #5 | Prediction of Titanic survivors, Feature engineering, Binary Classification, Classifiers comparison |
| Lab #6 | MLflow *, MLOps, Saving model, parameters and statistics; autologging |
| Lab #7 | TimeSeries, Darts, seasonality, NaiveDrift, NaiveSeasonal, ExponentialSmoothing, Theta |
| Lab #8 | Reinforcement Learning, Gymnasium, Q-learning, Reward function |
| Lab #9 | Text processing, Natural Languague Processing, NLP |
* to run Lab #6 you need to have mlflow installed and run a command:
mlflow server --host 127.0.0.1 --port 8080
in a result when you go in your browser to http://127.0.0.1:8080/ you should be able to see the following:
