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NREA Final Project: Correlations Between Elevation, Proportion of Coniferous Trees and Shannon’s Diversity Index
Project 2 - GPS Eagle data
This may be a first submission and may add another later in the day
McDonalds and Gamestop Assignment
In this assignment we will be looking at text and sentiment analysis and topic modelling in regards to McDonalds and Game Stop Reviews.
Data Science Capstone Next Word Presentation
Data Science Capstone Next Word Presentation
Clustering European Countries by Their Level of Development Using Different Algorithms: K-Means, PAM and Hierarchical
The primary goal of this study is to identify similarities among European countries in terms of their level of development. Two key variables are used for this purpose. The first, GDP per capita, reflects a country’s economic and financial prosperity. The second, the Human Development Index (HDI), captures the quality of human capital, including factors such as life expectancy and years of education. Together, these variables provide a comprehensive view of a country’s development level. To explore patterns in the data, multiple clustering algorithms will be applied: k-means, PAM (Partitioning Around Medoids) and hierarchical clustering (both agglomerative and divisive approaches). Using different methods will help verify the robustness of the results and uncover meaningful groupings among European countries.