Unit 2 | Ep 03: Outliers – Noise or Signal?

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Unit 2 | Ep 03: Outliers – Noise or Signal?

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About this listen

Welcome to Mindforge ML. In this episode, we investigate the rebels of your dataset: outliers.

An outlier can be a critical insight (fraud detection) or a disastrous error (sensor glitch). The difference lies in context. We move beyond simple deletion to explore detection and sophisticated treatment strategies.

Key topics:

Detection: Using Z-scores, IQR, and Isolation Forests to hunt down anomalies.
The Choice: Deciding when to remove, cap, or keep extreme values.
Visualization: Spotting problems with box plots and scatter plots.
Context: Why domain knowledge is your best tool for outlier management.

Stop blindly deleting data. Learn to read the extremes.

Series: Mindforge ML | Unit 2Produced by: Chatake Innoworks Pvt. Ltd.Initiative: MindforgeAI

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