AI Patasala Data Science Course Projects by Students

Fraud Detection Architecture

Problem Statement

  • With the advancements in technology, credit card fraudulent activities have become more prevalent
  • Credit card fraud leads to the loss of billions of dollars for consumers and financial companies
  • In 2020, US alone lost whopping $9.47 billion through illegal credit card transactions

Solution

The aim of this project is to build a model that is capable of detecting credit card fraudulent transactions.

  • We will be developing a fraud detection model using Machine Learning
  • This model can be built using different ML algorithms
  • We will also plot the respective performance curves for the models
  • We will learn how data can be analyzed and visualized to discern fraudulent transactions from other types of data

Fraud-Detection-Architecture
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Malware Prediction Architecture

Problem Statement

The dark world hackers are using system vulnerabilities to lure into systems and steal valuable data

  • Malware Prediction protects machines from damage before it happens
  • Malware prediction is one of the important step in the security of the computer systems

Solution

The aim of this project is to predict the system malware at an early stage to avoid data loss and

  • We will be developing a fraud detection model using Machine Learning
  • This model can be built using different ML algorithms
  • We will learn how to predict malicious behaviour using machine activity data

Fraud-Detection-Architecture
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Profitable Customer Segments

Problem Statement

Targeting potential users based on their peculiar interests can help enterprises in achieving the desired results.

  • But how to analyze and segment users based on their interest? This is a critical challenge for enterprises
  • Credit card fraud leads to the loss of billions of dollars for consumers and financial companies
  • In 2020, US alone lost whopping $9.47 billion through illegal credit card transactions

Solution

We can group customers into sections of individuals who share common characteristics. This approach is called Customer Segmentation

  • Customer Segmentation is one the most important applications of unsupervised learning
  • This technique can help enterprises in identifying several segments of customers
  • Companies can easily identify and target their potential user base
  • Customer segmentation helps in delivering personalize experiences to customers

Profitable-Customer-Segments
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