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.

Anomaly Detection in Manufacturing Spare Parts Using Machine Learning Techniques
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    Difficulty: Advanced

    Designed for those with a technical background or industry experience

  • Asset 1
    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.

What’s included

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Lifetime Access

Access this case study for life once completed

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Flexible Scheduling

Start learning online immediately, at your own pace

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Desktop Only

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Skills you will learn

Data Visualization

Data Management

Classification Model Building

Clustering Model Building

Associated Learning Tracks

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