It's a commonplace of artificial intelligence to say that machine learning, which depends on vast amounts of data, functions by finding patterns in data. The phrase, "finding patterns in data," in ...

This can happen even when the sparse data might be more predictive. Best machine learning model for sparse data To help combat these issues that arise with sparse data machine learning, there are a ...

Advancements in machine learning are revolutionizing mass spectrometry, enhancing small-molecule identification through ...

A new scientific machine learning framework developed by Professors Horacio D. Espinosa, Sridhar Krishnaswamy, and collaborators accurately predicts and inversely designs the mechanical behavior of ...

Professor Todd Murphey showed how robots can purposefully collect data to learn about the surrounding environment, rather than passively collecting data as they go about other tasks.

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

Our understanding of progress in machine learning has been colored by flawed testing data. The 10 most cited AI data sets are riddled with label errors, according to a new study out of MIT, and it ...

Recent study focused on predicting short birth intervals (defined as less than 33 months) among reproductive-age women in ...