Machine learning (ML) is a subset of artificial intelligence (AI) that involves using algorithms and statistical models to enable computer systems to learn from data and improve performance on a ...
One of the more tedious aspects of machine learning is providing a set of labels to teach the machine learning model what it needs to know. Snorkel AI wants to make it easier for subject matter ...
Testing Machine Learning: Insight and Experience from Using Simulators to Test Trained Functionality
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
The rapid development of deep learning in recent years is largely due to the rapid increase in the scale of data. The availability of large amounts of data is revolutionary for model training by the ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...
Just 10 years ago, most application development testing strategies focused on unit testing for validating business logic, manual test cases to certify user experiences, and separate load testing ...
Talk to any industry insider, and they’ll tell you that the landscape of software testing is undergoing a paradigm shift that’s rendering many existing practices inadequate. The pace of software ...
The majority of software development teams believe they don’t test well. They understand that the effect of quality defects is substantial, and they invest heavily in quality assurance, but they still ...
The artificial intelligence (AI) renaissance is largely due to advances in deep learning, a type of machine learning with architectural elements inspired by the biological brain. However, unlike the ...
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