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.
コースの説明
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.
技術
Python
言語
En
評価
章
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
