Creating a credit card fraud detector using SOM and deep learning

[Rohit-Sharma-RS]

An application that judges credit card fraud detection to benefit banks all over the world using deep learning and SOMs

[hackelite01]

To proceed with the idea of developing an application for credit card fraud detection using deep learning and Self-Organizing Maps (SOMs), I need some additional information:

1. Could you provide more specific requirements and expectations for the application?
2. Do you have any specific datasets in mind for training the model, or do you need assistance in finding one?
3. Which deep learning frameworks and tools do you prefer to use for this project?

These details will help in creating a clear plan and ensuring the project meets your needs.

[Rohit-Sharma-RS]

To proceed with the idea of developing an application for credit card fraud detection using deep learning and Self-Organizing Maps (SOMs), I need some additional information:

1. Could you provide more specific requirements and expectations for the application?
2. Do you have any specific datasets in mind for training the model, or do you need assistance in finding one?
3. Which deep learning frameworks and tools do you prefer to use for this project?

These details will help in creating a clear plan and ensuring the project meets your needs.

Here's a detailed outline of requirements, expectations, datasets, and frameworks for developing a credit card fraud detection application using deep learning and Self-Organizing Maps (SOMs):

Requirements and Expectations:

1. Python and a requirements.txt file will be also issued in the PR so as to clarify the requirements. 2.Detection Accuracy: Achieve a high detection accuracy (>90%) with minimal false positives.
2. Real-time Processing: Process transactions in real-time to prevent fraudulent activities.

Datasets:

• I already have the dataset available for this project.

Deep Learning Frameworks and Tools:

1. TensorFlow
2. Keras
3. Scikit-learn

Additional Libraries and Tools:

1. Data preprocessing: Pandas, NumPy
2. Data visualization: Matplotlib, Seaborn

Model Architecture:

SOM for clustering and anomaly detection in credit card data

Development Roadmap:

1. Data collection and preprocessing
2. Model development and training
3. Model evaluation and optimization

I am currently working on this project kindly assign it to me under hacktoberfest label if possible

[hackelite01]

Go with it!