Machine Learning - Learning Techniques, CNN, Languages and APIs

Stealing Machine Learning Models via Prediction APIs

Machine learning (ML) models may be deemed confidential due to their sensitive training data, commercial value, or use in security applications. Increasingly often, confidential ML models are being deployed with publicly accessible query interfaces. ML-as-a-service (“predictive analytics”) systems are an example: Some allow users to train models on potentially sensitive data and charge others f...

Machine Learning Techniques

Machine Learning for NLP: Supervised learning techniques

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Machine Learning for NLP: Unsupervised learning techniques

• So far we have seen supervised learning (of classification): – learning based on a training set where labelling of instances represents the target (categorisation) function – classifier implements an approximation of the target funtion – outcome: a classification decision • Unsupervised learning: – learning based on unannotated instances; – outcome: a grouping of objects (instances and groups...

The Past, Present, and Future of Machine Learning APIs

In this paper, we start off by summarizing the key evolutionary turning points of machine learning APIs and conclude by laying out our vision for the future of this key enabling component that can power tomorrow’s ubiquitous intelligent systems.