Anomaly Detection Engine (ADE) using LSTM Neural Networks
Leverage the Anomaly Detection Engine (ADE) to solve key challenges across various industries.
Marcin PRYS
Senior Data Engineer / Technical Leader at Inetum
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Quick outline
Introduction to the Anomaly Detection Engine (ADE)
Meet our speaker
1. Introduction
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Analyst with several years of experience in providing technological solutions aimed at increasing the business utility of data in an organization. University lecturer in the field of business analytics and data visualization.
Join us to explore practical ADE applications that can deliver significant benefits to your organization.
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2. Business context and objectives
Examples of ADE applications in various industries
Why ADE outperforms traditional methods
3. Technological solution overview
4. Practical use cases
Fraud detection, quality control, fuel consumption optimization
Business benefits and ADE efficiency
5. Results and impact
September 26th
at 12:00 PM (CEST)
6. Conclusion and next steps
Summary and future actions
Learn how ADE can assist in:
Detecting fraud in the financial sector – Identify suspicious transactions and customer behaviors, minimizing the risk of financial loss.
Quality control in production – Spot defective items during the production process, reducing waste and enhancing product quality.
Maintenance management – Monitor the usage of consumable materials and detect anomalies that could indicate technical issues before they lead to breakdowns.
Optimizing fuel consumption in logistics and aviation – Uncover fuel misuse and optimize routes to lower operational costs and increase efficiency.
