Case Study

Detecting Credit Card Fraud Using Feature Engineering

The case study will allow learners to understand the concept of Feature Engineering Techniques for transforming the data in a format suitable for training machine learning models.

Detecting Credit Card Fraud - Feature Engineering Techniques
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    Difficulty: Advanced

    Designed for those with a technical background or industry experience

  • Asset 1
    Duration: Approximatley 2 hours

Case Overview

  • The case enables the learner to gain practical experience by applying the fraud detection model to real world data that can classify a transaction as fraudulent or legitimate with a high degree of accuracy.
  • Deep understanding of Feature engineering technique, which is an integral step before model building that improves the model performance.
  • Understanding the theoretical concept behind categorical encoding methods such as label encoding and one hot encoding.
  • The case helps in understanding various techniques such as feature transformation, data scaling, binning to improve model stability.

What’s included

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Flexible Scheduling

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Desktop Only

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Skills You Will Learn

User interface

Data Preprocessing

Data Mining

Data Visualization

Data Management

Feature Engineering

Associated Learning Tracks

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