Fraud Detection – Flagging Suspicious Transactions with NLP Techniques

What You’ll Learn

• NLP Fundamentals: Understand how Natural Language Processing (NLP) applies to fraud detection.
• Tools & Techniques: Master Count Vectorizer, TF-IDF, and machine learning models.
• Preprocessing Skills: Learn to clean transaction data for anomaly detection.
• Practical Modeling: Build, train, and evaluate fraud detection models using real-world data.
• Metrics Mastery: Evaluate models using accuracy, precision, recall, and F1-score.

Requirements

• Basic Python Skills: Familiarity with Python programming.

• Data Basics: Understanding of datasets and common preprocessing tasks.

• Enthusiasm to Learn: A desire to apply data science to real-world problems.

Description

This course equips you with tools to flag suspicious transactions by applying NLP techniques.

• Real-world Focus: Learn from actual fraud scenarios.

• Integration: Combine text analysis with advanced machine learning.

• Career Growth: Build a strong foundation for fraud detection roles in finance or data science.

Who This Course is For

• Business Analysts: Detect patterns in transaction data.

• Data Scientists: Expand your NLP toolkit.

• Fraud Prevention Teams: Gain insights into modern fraud techniques.

• Aspiring Professionals: Launch a career in data-driven fraud detection.