Program Outline
Building Deep Learning-Based Anti-Fraud Applications
Focuses on building anti-fraud applications using deep-learning techniques for financial and transaction-oriented scenarios.
Delivery
Virtual, On-site, or Hybrid
Duration
8 hours
Product
Deep Learning Frameworks
Role
Data Scientist
NVIDIA
Deep LearningBuilding Deep Learning-Based Anti-Fraud Applications
Deep Learning Frameworks
Best Fit
Audience Profile
Who This Program Is For
Built for teams building AI-led fraud-detection systems.
Overview
Program Summary
Official NVIDIA DLI workshop for anti-fraud application development using deep learning methods.
Course Outline
Complete Module Sequence
Review the full module sequence for this program, including the primary topic coverage in each module where available.
1Module 1
Create anti-fraud AI solutions
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Module 1
Create anti-fraud AI solutions
Explore deep-learning approaches for transaction risk and fraud detection.
- Fraud signal modeling
- Deep-learning anti-fraud workflows
Coverage Areas
Topic Coverage
Coverage Item 1
Fraud signal modeling
Coverage Item 2
Deep-learning anti-fraud workflows
Customization
Adapt This Program for Your Team
We can adapt this program around your team structure, platform priorities, delivery goals, and the scenarios your people need to work through in practice.
- •Use your fraud or transaction-monitoring use case
- •Add deployment and alerting logic
