Identifying Undervalued Football Players
Daniil Lypenets
Python
8 Chapters
0 Studying now
A hands-on, project-based course guiding learners through the process of cleaning, analyzing, modeling, and interpreting the FIFA 22 player dataset to identify undervalued footballers and distinct playing styles using Python and essential data science techniques.
Descripción del curso
A hands-on, project-based course guiding learners through the process of cleaning, analyzing, modeling, and interpreting the FIFA 22 player dataset to identify undervalued footballers and distinct playing styles using Python and essential data science techniques.
Tecnología
Python
Lengua
En
Calificación
Capítulos
8
Data Inspection & Cleaning
Exploring Market Value
Position Normalization
Market Value Baseline Model
Moneyball — Undervalued Players
Playing Style Clustering
Interpreting Playing Styles
Final Scouting Shortlist
0%
Data Inspection & Cleaning
Exploring Market Value
Position Normalization
Market Value Baseline Model
Moneyball — Undervalued Players
Playing Style Clustering
Interpreting Playing Styles
Final Scouting Shortlist
