Technical Blog from our Data Science Team

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Showing posts with tag: machine learning

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Synthetic data in machine learning

Machine learning algorithms are currently applied in multiple scenarios in which unbalanced datasets or overall lack of sufficient training data lead to their suboptimal performance. For example, approaches focusing on disease prediction are often affected because data in the health sector is generally difficult to acquire and disease training examples are limited. Fraud detection in

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Generative Adversarial Networks – when AI gets creative

Since Frank Rosenblatt introduced the Perceptron in 1958, neural networks have significantly evolved and taken the world by storm. Their ability to model complex, non-linear relationships that exist in data, led to novel neural network architectures, able to outperform humans in various challenging tasks like face recognition, disease prognosis and playing video games. However, even

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