But for machine learning, the bigger the better — and that usually translates into large public domain datasets. Either way Singhal said, the key “is to build the in-house tech infrastructure ...

“Developing new machine learning ... measured in multiple modalities at multiple time points. For this year’s competition, Cellarity generated a 300,000-cell time course dataset of CD34 ...

SUNNYVALE, Calif.--(BUSINESS WIRE)--Yahoo Inc. (NASDAQ: YHOO) today announced the public release of the largest-ever machine learning dataset to the academic research community. With this release ...

Yahoo announced this morning that it’s making the largest-ever machine learning dataset available to the academic research community through its ongoing program, Yahoo Labs Webscope.

But these AI and machine learning datasets — like the humans that designed ... In AI, benchmarking entails comparing the performance of multiple models designed for the same task, like ...

Amazon SageMaker does hyperparameter tuning but doesn’t automatically try multiple models or perform feature engineering. Azure Machine Learning has both AutoML, which sweeps through features ...

By using multiple forms of machine learning systems ... Once set up, the ML system applies itself to a dataset or problem, spots situations, and solves problems. It uses algorithms to parse ...

Rajan's group has used a full-scale version of the dataset to research behavior modeling, recommender systems and large-scale and distributed machine learning, among other topics. "We hope that this ...