Applications
Business Intelligence Dashboards & Machine Learning Models
Embedded Files
Advanced statistical methods are known to have two traits: 1) Second to none power and versatility for analysis across essentially any domain. 2) Seemingly locked behind a wall of complication notation that requires years of experience to master. In this project, I explore how this challenge can be overcome with the design of an intuitive business intelligence dashboard. The goal here is not a particular piece of analysis, but providing easy access to techniques otherwise reserved for experts.
Leveraging the BallDontLie API, this dashboard provides up to date information on NBA games for the past 75 years. Implementing a careful orchestration of data slicers, the dashboard allows for all sorts of comparisons: Compare Abdul-Jabbar's time with the Lakers against the stats of the entire Celtic team. Or select your favorite combinations of players to build your super team and compare against alternatives.Â
Hierarchical machine learning models are constituted by layers of models. These allow for incremental categorization of hierarchical class structures. (E.g. predicting 'mammal' before 'dog'.) Doing so speeds up performance by dividing the difficulty of the problem as well as the data that each sub-model needs to process. Additionally, it provides predictions at intermediate levels thereby increasing insights and facilitating hyperparameter tuning.
Google Sites
Report abuse