KMeans Cluster Analysis: Data Science Project With Python
In this tutorial video using #python for data science, we are clustering customers using #KMeans #clustering and the essential Python libraries: pandas, scikit-learn and seaborn. I am walking you through a unique machine learning #project using the transactional data of online casino players, performing #featureengineering to convert customer transactional data to customer features.
The first part of the #datascience #project can be watched here:
Exploratory Data Analysis in Python: Data Science Project: • Exploratory Data Analysis In Python: Machi...
Contents:
00:00 - Introduction
02:23 - Data understanding
04:00 - Cluster analysis simply explained
05:11 - Feature engineering: for time series to customer features
18:02 - Join multiple pandas DataFrames
19:15 - Replace missing values with constant in pandas DataFrame
21:00 - Feature visualization with pairplot
23:07 - How to select the number of clusters for kmeans cluster analysis
24:42 - Elbow method for cluster selection
26:24 - Interpreting Silhouette plot
27:46 - Feature transformation with logarithm
28:35 - Cluster analysis
32:30 - Scatter plots
33:10 - Reverse the transformation for scale
38:43 - Conclusion
Datasets: https://data.mendeley.com/datasets/9j...
Give a 🌟 to the code repository: https://github.com/giraffa-analytics/...
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