H13-311_V3.0 Exam Dumps - H13-311_V3.0
Which of the following descriptions about the Recurrent Neural Network (RNN) is correct?
When dealing with actual problems, when should machine learning be used in the following situations?
In deep learning tasks, when encountering data imbalance problems, which of the following methods can we use to solve the problem?
In the deep learning neural network, the perceptron is the simplest neural network. The correct statement about its structure is:
The pooling layer in the convolutional neural network can reduce the size of the lower layer input. Common pooling is:
Only matrix A and matrix B have the same number of rows and columns. A and B can be added.
The word recognition in the speech recognition service refers to the synchronous recognition of short speech. Upload the entire audio at once, and the recognition result will be returned in the response.
When training the network, we often encounter many problems. For the problem of gradient disappearance, we can alleviate the problem by choosing which of the following functions to use?
The following code was used when compiling the model:model.compile(optimizer='Adam,loss='categorical.crossentropy',metrics=[tf.keras.metrics.accuracy]), currently using evaluate When the method evaluates the
model, which of the following indicators will be output?
In deep learning, if the neural network has a large number of layers, the problem of gradient disappearance is more likely to occur. Strictly speaking, in which of the following links does the sample disappearance problem
occur?
Which of the following options is not the- session mode used by Tensorflow?
Which of the following statements about passport recognition services are correct?
Facing industry research and full scenarios AI The huge gap between applications, MindSpore Bridging the application gap to help inclusiveness AI Of technological innovation does not include which of the following?
Gyclic neural networks are more suitable for dealing with image recognition problems.
What is the incorrect relationship between neural networks and deep learning?
The model composed of machine learning algorithms cannot represent the true data distribution function on a theoretical level. Just approach it.
L1 with L2 Regularization is a method commonly used in traditional machine learning to reduce generalization errors. The following is about the two. The right way is:
On Huawei Cloud EI Which of the following can be AI Technology is integrated into the application scenarios of all walks of life AI The advantages of technology to improve efficiency and improve experience.
There are many types of neural networks in deep learning. The following neural network information is one-way propagation:
Linear regression in 3 The fitted surface in the dimension above dimension is?
What are the results returned by the if conditional statements in the Python language? (Multiple choice)
What are the commonly used gradient descent optimization functions? (Multiple Choice)
Feedforward neural network is a simple neural network, each neuron is arranged hierarchically, it is currently one of the most widely used and fastest growing artificial neural networks. The following statement about
feedforward neural networks is correct:
What does factors that promote the development of artificial intelligence not include?
What of the following does belong to convolutional neural network (CNN)? (Multiple Choice)
When we describe the house, we usually use the attributes such as residential area, house type, decoration type, etC. If we use plain With Bayes as a model, we assume that there is no relationship between attributes.
HiAI Mobile computing platform provides rich upper-level functional services API, Can run efficiently on mobile devices.
Which of the following options is not a reason for traditional machine learning algorithms to promote the development of deep learning?