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Huawei Exam H13-311_V3.5 Topic 7 Question 12 Discussion

Actual exam question for Huawei's H13-311_V3.5 exam
Question #: 12
Topic #: 7
[All H13-311_V3.5 Questions]

In machine learning, which of the following inputs is required for model training and prediction?

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Suggested Answer: B

In machine learning, historical data is crucial for model training and prediction. The model learns from this data, identifying patterns and relationships between features and target variables. While the training algorithm is necessary for defining how the model learns, the input required for the model is historical data, as it serves as the foundation for training the model to make future predictions.

Neural networks and training algorithms are parts of the model development process, but they are not the actual input for model training.


Contribute your Thoughts:

Carole
2 days ago
Manual program? What is this, the 1980s? We're in the age of machine learning, baby!
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Stefany
3 days ago
Neural network? Isn't that what they use to power self-driving cars? Sign me up for that!
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Eun
14 days ago
I believe neural network is also required for model training and prediction, as it is the backbone of many machine learning models.
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Lazaro
14 days ago
Training algorithm is key. You can't just throw data at a model and expect it to work. The algorithm is what makes the magic happen.
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Felix
17 days ago
I agree with Talia. Historical data helps the model learn patterns and make predictions.
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Talia
22 days ago
I think historical data is required for model training and prediction.
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Jesusa
24 days ago
Historical data, of course! Without real-world data, how can the model learn anything meaningful?
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Rana
11 days ago
B) Historical data
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Beatriz
12 days ago
Historical data, of course! Without real-world data, how can the model learn anything meaningful?
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