Case Study

Predicting Credit Card Spend – Artificial Neural Network

The case study introduces to the potential of deep learning model an emerging artificial intelligence technology to assess the probability of credit card delinquency based on the client’s personal traits and purchasing habits.

Build a Regression Tree for Predicting Spend on Credit Card
  • 3 bar graph
    Difficulty: Advanced

    Designed for those with a technical background or industry experience

  • Asset 1
    Duration: Approximately 3 hours

Case Overview

  • The case familiarizes the learner with a comprehensive understanding of deep learning techniques for banking professionals to identify the credit card spend on customers. based on various financial indicators.
  • Understand key insights about the data by implementing various data visualization methods.
  • Gain understanding of data type conversion technique such as one hot encoding, that converts categorical data to numerical data.
  • The case enables the learners to use/apply neural network models to predict the spending patterns of the customers based on the various attributes.

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 Management Techniques

Deep Learning

Data Aggregation Techniques

ANN Model Building

Shallow and Deep Neural Networks

Associated Learning Tracks

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