LaundroGraph: Using deep learning to support anti-money laundering efforts
In recent years, deep learning techniques have proved to be highly valuable for tackling countless research and real-world problems. Researchers at Feedzai, a financial data science company based in Portugal, have demonstrated the potential of deep learning for the prevention and detection of illicit money laundering activities.
E-commerce sales have skyrocketed as more people shop remotely, spurred by the pandemic. But this surge has also led fraudsters to use the opportunity to scam retailers and customers, according to David Sutton, director of analytical technology at fintech company Featurespace. The company, headquartered in the U.K., has developed AI-powered…
Deep learning is a subset of machine learning that has become a cornerstone in many technological breakthroughs. At the core of deep learning, it’s a model inspired by the human brain, which we call a neural network. Contrary to the traditional machine learning model, deep learning can automatically find feature…
The most popular deep learning libraries in Python for research and development are TensorFlow/Keras and PyTorch, due to their simplicity. The scikit-learn library, however, is the most popular library for general machine learning in Python. In this post, you will discover how to use deep learning models from PyTorch with…