Examples of using Machine learning models in English and their translations into Italian
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Ecclesiastic
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Computer
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Programming
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Official/political
One of the machine learning models.
Automatically convert machine learning models to standalone C/C++ code.
Analyse, assess and interpret the results of machine learning models.
Automatically convert machine learning models to standalone C/C++ code Customers' Choice.
Amazon SageMaker to quickly build, train and deploy machine learning models at scale;
Machine learning models for interaction modeling: autobiographical memories(8).
Improve and simplify machine learning models.
Enhance machine learning models by re-learning models with proprietary data.
Beta Design and deploy machine learning models.
Microsoft uses machine learning models to classify and extract relevant information from SMS on your phones.
This method works for machine learning models.
Dedicated to Machine Learning models in the fraud field. During this speech the Customer describes its experience.
Amazon SageMaker to quickly build, train and deploy machine learning models at scale;
Comparisons of different machine learning models to quickly identify the best one.
How Google aims to simplify the grunt work behind AI and machine learning models.
Bitdefender HyperDetect contains machine learning models and stealth attack detection technology.
Core ML 3 supports the acceleration of more types of advanced, real-time machine learning models.
And for the first time, developers can update machine learning models on-device using model personalisation.
and develop machine learning models.
Our new machine learning models make it more effective, and
makes it easy for developers to integrate machine learning models into their apps.
Provides human input to machine learning models with real-time preview showing the impact of a sensitivity
improved its effectiveness with new machine learning models.
Acronis Ransomware Protection monitors your computer in real-time, using machine learning models to differentiate between normal and suspicious activities.
and deploy machine learning models.
These instances will enable developers to formulate machine learning models faster to improve the performance of the domain assessment tool.
Also, the machine learning models in these projects can be solicited with open calls, whereby researchers compete to create machine learning models with the greatest predictive performance.
whereby researchers compete to create machine learning models with the greatest predictive performance.
These instances will enable developers to formulate machine learning models faster to improve the performance of the domain assessment tool.