Examples of using Deep learning model in English and their translations into Chinese
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Try to imagine deep learning model as a child.
For the next steps, we will focus on the deep learning model.
How to build a deep learning model in 15 minutes?
These adversarial examples are often used to attack a deep learning model.
How to build a deep learning model in 15 minutes?
When layers get greatly large, model becomes a deep learning model.
In a deep learning model, features are identified by the A.I. itself.
To demonstrate it they trained a deep learning model to recognize handwritten numerals.
In contrast,keras provides a simple and convenient way to build a deep learning model.
New AI deep learning model allows earlier, more accurate ozone….
The company says it hasmanaged to reduce the training time of a ResNet-50 deep learning model on ImageNet from 29 hours to one.
When you train a deep learning model, two main operations are performed:.
The Japanese insurance company, AXA, could increase its prediction rate of auto accidents from40 percent to 78 percent by applying a deep learning model.
By applying my Deep Learning model the bank may significantly reduce customer churn.
With this training set,Google intern Zbigniew Wojna spent the summer of 2016 developing a deep learning model architecture to automatically label new Street View imagery.
The accuracy of a deep learning model depends to a very great extent on the quality of the training data.
When a deep learning model has been trained, it is not always clear how it goes about making decisions[6].
An autoencoder is an unsupervised deep learning model that attempts to copy its input to its output.
A Deep Learning model(such as a Convolutional Neural Network) does not try to understand the entire problem at once.
In this tutorial, we will build a Python deep learning model that will predict the future behavior of stock prices.
Train a deep learning model with bad data introduces the very real possibility of creating a system with inherent bias and incorrect or objectionable outcomes.
In this tutorial, you will build a deep learning model that will predict the probability of an employee leaving a company.
To tune a deep learning model correctly requires immense data sets, graphic processing units or tensor processing units, and time.
You couldn't have had a deep learning model 30 years ago, because you didn't have the data and the computing power.”.
In constrast, our new deep learning model actually builds up a representation of whole sentences based on the sentence structure.
The research uses a deep learning model to allow earlier detection of the incidents and stages that often lead to heart failure within 6-18 months.
The paper's results show the deep learning model can read scans at the level of experienced radiologists and improve the consistency in their density assessments.
