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Industry Use Case
Anomaly Detection in Manufacturing Spare Parts Using Machine Learning
This project exposes the learner to the concepts of Advanced Supervised Machine Learning Models.
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Difficulty: AdvancedDesigned for those with a technical background or industry experience
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Duration: Approximately 3 hours
Course Overview
- Classification algorithms can play a crucial role in detecting anomalous data points based on the different attributes.
- Manufacturing process often involves quantities in bulk and so there is always a possibility of having certain components as defective.
- One of the most significant challenges faced by manufacturing firms is that their systems can detect only 20% of irregularities in advance.
- Learn how to build and apply a robust classification model which can efficiently detect the anomalous parts and prevent unnecessary wastage of resource and time.
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Skills you will learn
Associated Learning Tracks
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