Visualizing Machine Learning#

You’ll learn about improving customer retention, understanding black box models, and using clustering for market segmentation:

• Churn Reduction: Use decision trees to identify customers likely to leave.
• Cost Efficiency: Compare customer acquisition vs. retention costs.
• Model Improvement: Apply SVMs and neural networks for better accuracy.
• Project Challenges: Understand issues with black box models in implementation.
• K-Means Clustering: Segment markets using demographic data.
• Data Visualization: Interpret clustering results using maps and charts.
• Correlation Analysis: Identify relationships between currency exchange rates.
• Tool Proficiency: Utilize Excel, Python, and JavaScript for analysis and communication.
• Practical Application: Tailor marketing strategies based on cluster characteristics.

Here are the links used in the video:

• Visualizing-Forecast-Models.xlsx - the spreadsheet used in the video