Lecture "Applied data science: Application" includes content: digital transformation, data science lifecycle, data science application,... We invite you to consult!

Lecture "Applied data science: Validation" includes content: validation set approach; overfitting; cross-validation; data leakage; nested cross-validation; bootstrapping;... We invite you to consult!

Lecture "Applied data science: Clustering" includes content: Exemplary technique - K-means clustering; Exemplary technique - Hierarchical clustering; Practical issues in clustering; Case study;... We invite you to consult!

Lecture "Applied data science: Regularisation" includes content: variable subset selection, shrinkage methods, dimension reduction, considerations in high dimensions,... We invite you to consult!

Lecture "Applied data science: Classification" includes content: Classification - logistic regression review ; classification evaluation metrics; the expected value framework;... We invite you to consult!

Lecture "Applied data science: Introduction" includes content: data science application, history data science, history statistisc, history big data, data science lifecycle,... We invite you to consult!

Lecture "Applied data science: Evaluation, deployment, ethics" includes content: evaluation validation components, evaluation dataset, simpon's paradox, some ethical issues in ML,... We invite you to consult!

Lecture "Applied data science: Linear regression (review)" includes content: the regression model formulation, understanding the regression results, potential problems in regression model,... We invite you to consult!

Lecture "Applied data science: Exploratory data analysis" includes content: definitions; data types; steps in Exploratory Data Analysis (EDA); EDA in real-life practice;... We invite you to consult!

Lecture "Applied data science: Learning process and Bias – variance tradeoff" includes content: learning process, bias – variance tradeoff, variance tradeoff, bias variance,... We invite you to consult!