영어에서 Learning models 을 사용하는 예와 한국어로 번역
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Successful machine learning models are trained using data that has been labeled to teach the model how to make correct decisions.
Recently, advances in Airbnb's machine learning infrastructure have lowered the cost significantly to deploy new machine learning models to production.
Powered by state-of-the-art machine learning models, Amazon Comprehend can discover insights from unstructured text like social media posts,
The concept of rationality of several machine learning models merging with their further transfer learning has been proposed and proved later.
Many traditional machine learning models can be understood as special cases of neural.
Existing machine learning models developed on Amazon SageMaker can work seamlessly with this new capability without any changes.
JPEG to RAW's machine learning models expand the sRGB colorspace to ProPhoto RGB, which is even better than a regular RAW file!
Machine learning models have been around for ages,
As organizations rely more on artificial intelligence and machine learning models, how can they ensure they're trustworthy?
While machine learning models can be invaluable,
Learning models for those actions is the most important property for this type of technology.".
Learning models for those actions is prime real-estate for this kind of technology.”®.
The deep learning models, including GoogleNet and Microsoft Research's ResNet, were initially created to detect and classify objects in traditional photo and video imagery.
Deep learning models are even more data hungry than previous algorithms favored by data scientists.
But as organizations become more reliant on machine learning models, how can humans be sure that these recommendations are trustworthy?
While machine learning models can be very useful,
Deep Learning models usually require a lot of data to train properly.
what the flipped classroom and personalised learning models highlight is a strong turn towards classrooms centred around technology.
Although the feature is available, at least one ATP policy must be defined in order for the ATP machine learning models to work.
With powerful re-engagement machine learning models, Liftoff retargeting campaigns result in more in-app engagement& conversions for all app categories.