Examples of using Deep learning models in English and their translations into Indonesian
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Build end-to-end deep learning models and fine-tune to underwater training data.
On September 28th, 2016, the seven-member Google researchteam announced YouTube-8M leveraging state-of-the-art deep learning models.
Deep learning models achieve state-of-the-art accuracy, sometimes exceeding human-level performance.
This rich data is used to train deep learning models to interpret human behavior the way people do.
Deep learning models such as convolutional neural networks, or CNNs, are used to automatically learn an object's inherent features in order to identify that object.
You need a lot of data to train deep learning models because they learn directly from the data.
AWS and Microsoft last month announced plans for Gluon, a new interface in Apache MXNet that allows developers to build andtrain deep learning models.
This is used to train deep learning models to interpret human behaviour the way people do.
Facebook and Microsoft are today introducing Open Neural Network Exchange(ONNX) format,a standard for representing deep learning models that enables models to be transferred between frameworks.
These deep learning models are restricted in their capacity to“reason”, for example, to do long chains of deductions, or streamlining a method to land at an answer.
You need lots of data and speed to train deep learning models because they learn directly from the data.
Headquartered in San Francisco, Calif., Kinetica is the provider of the only GPU database to combine data warehouse, advanced analytics, visualizations,and is optimized for running machine learning and deep learning models.
You need masses of facts to train deep learning models due to the fact they learn immediately from the data.
This unique data marketplace gives enterprises deep insight into their customers and prospects andcan be activated through a suite of adaptive intelligent applications powered by deep learning models that operate at web-scale to learn about users and their behaviors.
NASCAR plans to use Amazon SageMaker to train deep learning models against 70 years of historical footage to enhance metadata and video analytics.
The AI takes aspiring AI engineers from a basic introduction ofAI to mastery of the skills needed to build deep learning models for AI solutions that exhibit human-like behavior and intelligence.
Most modern deep learning models are based on artificial neural networks, specifically, Convolutional Neural Networks(CNN)s, although they can also include propositional formulas or latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep Boltzmann machines.
As more and more data is gleaned and assessed by deep learning models, personalized medicine may well become a commonplace.
The availability of Cray supercomputers in Azure empowers researchers, analysts,and scientists with the ability to train AI deep learning models in fields such as medical imaging and autonomous vehicles in a fraction of the time.
Amazon Translate is aneural machine translation service that uses deep learning models to deliver more accurate and natural sounding translation than traditional statistical and rule-based translation algorithms.
But many linguists think that language is best understood as a hierarchical tree of phrases,so a significant amount of research has gone into deep learning models known as recursive neural networks that take this structure into account.
Already, Microsoft has famously demonstrated how well its deep learning models can handle real-time voice translation from one language to another.
All the content produced by theAI Copywriter is the result of applying deep learning models, trained with large volumes of quality content created by humans.
Neural machine translation is aform of language translation automation that uses deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms.
This is a neural machine translation service,which is a form of language translation automation that uses deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms.
For those of you that didn't know, neural machine translation is aform of language translation automation that uses deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms.
Keras: Keras is an open source library written in python for the neural network,it was developed to make implementing deep learning models as fast and easy as possible for research and development and was released under the permissive MIT license.
Together, we have built privacy-robust data partnerships to better understand moviegoers,and have developed in-house deep learning models that train on granular customer data and movie scripts to identify the basic patterns in audiences' preferences for different types of films.