Tag: machine

Oracle open-sources Java machine learning library

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On the lookout to fulfill enterprise wants in the equipment understanding place, Oracle is building its Tribuo Java equipment understanding library readily available no cost less than an open resource license.

With Tribuo, Oracle aims to make it a lot easier to build and deploy equipment understanding versions in Java, related to what previously has happened with Python. Launched less than an Apache 2. license and made by Oracle Labs, Tribuo is accessible from GitHub and Maven Central.

Tribuo presents normal equipment understanding functionality which includes algorithms for classification, clustering, anomaly detection, and regression. Tribuo also includes pipelines for loading

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Unmasking the Black Box Problem of Machine Learning

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Typical Chartered faucets Truera to pull back the veil for improved transparency on how its knowledge will get analyzed and the predictions algorithms make.

Economical and banking solutions firm Typical Chartered turned to a design intelligence system to get a clearer photo of how its algorithms make choices on customer knowledge. How machine understanding arrives to conclusions and generates results can be a bit mysterious, even to the groups that acquire the algorithms that drive them — the so-referred to as black box problem. Typical Chartered selected Truera to support it lift absent some of the obscurity and potential biases

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It’s deadline day for the Computing AI & Machine Learning Awards

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The Computing AI & Device Mastering Awards recognise the finest companies, people today, and assignments in the AI area nowadays. The awards address each and every corner of the marketplace: stability, ethics, information assessment, innovation and far more, as well as showcasing the movers and shakers: the technological innovation heroes and assignments that deserve marketplace-large praise.

The awards will consider area at the glamorous Waldorf Hilton in London on Tuesday twenty Oct and nowadays is the ultimate day for submitting your entries.

How to enter

To submit your entry type and submission, make sure you stop by the AI &

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MLops: The rise of machine learning operations

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As hard as it is for data scientists to tag data and develop accurate machine learning models, managing models in production can be even more daunting. Recognizing model drift, retraining models with updating data sets, improving performance, and maintaining the underlying technology platforms are all important data science practices. Without these disciplines, models can produce erroneous results that significantly impact business.

Developing production-ready models is no easy feat. According to one machine learning study, 55 percent of companies had not deployed models into production, and 40 percent or more require more than 30 days to deploy one model. Success brings

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Machine learning helps scientists interpret crystal patterns

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For experts and engineers, the most effective way to realize a new or not known material—whether it is an alloy, a pharmaceutical, or a meteorite—is to delve into its atoms.

Tactics such as X-ray diffraction, microscopy, and spectroscopy can give insights into a material’s crystal orientation, construction, and chemical composition, facts that is typically very important for predicting the overall performance of state-of-the-art components such as nuclear fuels.

But, examining knowledge from these approaches, especially diffraction designs, is a time-consuming procedure.

The model has been evaluated on components with a vary of symmetries. This picture displays the diffraction pattern of

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