Skip to main content

Results for: machine learning

Show:
Selected page 1
https://azure.microsoft.com/en-us/overview/what-is-machine-learning-platform

Machine learning (ML) is the process of using mathematical models of data to help a computer learn without direct instruction. It’s considered a subset of artificial intelligence (AI). Machine learning uses algorithms to identify patterns within data, and those patterns are then used to create a data model that can make predictions.

https://azure.microsoft.com/en-us/services/machine-learning

Build responsible machine learning solutions. Access state-of-the-art responsible machine learning capabilities to understand, control, and help protect your data, models, and processes. Explain model behavior during training and inferencing, and build for fairness by detecting and mitigating model bias.

https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet

Using a 9GB Amazon review data set, ML.NET trained a sentiment analysis model with 95% accuracy. Other popular machine learning frameworks failed to process the dataset due to memory errors. Training on 10% of the data set, to let all the frameworks complete training, ML.NET demonstrated the highest speed and accuracy.

https://www.microsoft.com/en-us/research/podcast/machine-learning-molecular-simulation...

A lot of the work we’ve been doing has been using machine learning driven by, uh, experimental data, but we’re very excited to augment that and amplify that by using molecular simulation, where we’re creating data more from first-principle simulation of the—the quantum physics of molecules of proteins folding and interacting with other ...