Examples of using Deep learning in English and their translations into Vietnamese
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So what can Deep Learning do?
Deep Learning(DI) is a subset of Machine Learning(ML.
Applying deep learning in NLP.
The company decided to tackle this problem using deep learning.
So, what deep learning can exactly do?
People also translate
Recent breakthroughs in AI are largely attributable to a technique called deep learning.
Now's the time to do deep learning in the cloud.
However, deep learning will not be restricted to technical specialists alone.
A day at the beach: Deep learning for a child.
Deep learning is also being applied to the recognition of vehicles and people.
Keras is a widely-used deep learning library written in Python.
Deep learning can also help scientists predict earthquakes and other natural disasters.
Deeplearning4j, an open-source,distributed deep learning framework written for the JVM.
The“Deep” in Deep Learning refers to having more than one hidden layer.
Many of the papers,data sets, and software tools related to deep learning have been open sourced.
We also use deep learning neutral network as GANS, DNNS.
What T2T doesn't do is provide a larger context beyond TensorFlow for how to organize a deep learning project.
Ng put the“deep” in deep learning, which describes all the layers in these neural networks.
The New York Times also showed in this article another extraordinary result of deep learning which I'm going to show you now.
The methods for deep learning are based on the same principles that power the human brain.
Expect ever more announcements and activity in this space as deep learning continues to find new adherents in the enterprise.
They use Deep Learning technology at its most effective- for its ability to classify and recognise thousands of‘features.
It supports almost 30 languages, provides easy deep learning integration and promises robustness and high accuracy.
Deep learning problems are becoming crucial nowadays since more and more use cases require considerable effort and time.
And you will still get the same features for ray tracing and deep learning(for example DLSS), although not so much of each core type.
For example,“Bob, what is the definition of“Artificial Intelligence?” or“Jane,explain the difference between Machine Learning and Deep Learning?.
One fundamental principle of deep learning is to do away with hand-crafted feature engineering and to use raw features.
I'm excited to pen down a series of articles where I will break down the basic components that every deep learning enthusiast should know thoroughly.
Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of complicated propositional formulas.
Rather than training a neural network, MENNDL- the Multi-node Evolutionary Neural Networks for Deep Learning- creates the network itself.