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    deep learning

    Deep learning (DL) is a branch of artificial intelligence and a machine learning (ML) technique based on artificial neural networks. Deep learning algorithms use multiple layers (hence the name) to process and analyse information. This can be used for tasks such as image and speech recognition and natural language processing. In other words, for processes that humans perform intuitively and that cannot be calculated using formulae. The necessary complexity is achieved using a digital layer model. In DL complex learning effects – and decisions based on them – are based on the combination of many small, simple decisions and learning effects.

    Deep learning has greatly improved the results of machine learning in many areas, but it is also much more resource-intensive than non-deep ML methods, i.e. single-layer neural networks, or other algorithms that do not require neural networks at all. (more…)

    defensive distillation

    Defensive distillation is an adversarial training technique used in the field of machine learning, specifically in the context of deep learning. The technique protects neural networks from adversarial attacks and makes an algorithm’s classification process more flexible so the model is less vulnerable to exploitation. (more…)