Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

Ben Khalesi writes about where artificial intelligence, consumer tech, and everyday technology intersect for Android Police. With a background in AI and Data Science, he’s great at turning geek speak ...

Semi-supervised learning merges supervised and unsupervised methods, enhancing data analysis. This approach uses less labeled data, making it cost-effective yet precise in pattern recognition.

Machine learning has proven to be very efficient at classifying images and other unstructured data, a task that is very difficult to handle with classic rule-based software. But before machine ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More At the advent of the modern AI era, when it was discovered that powerful ...

This is part Three of my series based on Lomit Patel’s “Lean AI” (O’Reilly, ISBN:978-1-492-05931-8). The first two described supervised and unsupervised learning and gave examples of business ...

ACM, the Association for Computing Machinery, today named Maria Florina "Nina" Balcan of Carnegie Mellon University the recipient of the 2019 ACM Grace Murray Hopper Award for foundational and ...