AIP-210 試験問題を無料オンラインアクセス

You are developing a prediction model. Your team indicates they need an algorithm that is fast and requires low memory and low processing power. Assuming the following algorithms have similar accuracy on your data, which is most likely to be an ideal choice for the job?

• A.Deep learning neural network
• B.Support-vector machine
• C.Ridge regression
• D.Random forest

Which of the following can benefit from deploying a deep learning model as an embedded model on edge devices?

• A.Guaranteed availability of enough space
• B.Reduction in latency
• C.A more complex model
• D.Increase in data bandwidth consumption

You have a dataset with thousands of features, all of which are categorical. Using these features as predictors, you are tasked with creating a prediction model to accurately predict the value of a continuous dependent variable. Which of the following would be appropriate algorithms to use? (Select two.)

• A.K-nearest neighbors
• B.Ridge regression
• C.Logistic regression
• D.K-means
• E.Lasso regression

You train a neural network model with two layers, each layer having four nodes, and realize that the model is underfit. Which of the actions below will NOT work to fix this underfitting?

• A.Increase the complexity of the model
• B.Train the model for more epochs
• C.Get more training data
• D.Add features to training data

Which of the following is TRUE about SVM models?

• A.They use the sigmoid function to classify the data points.
• B.They can be used only for classification.
• C.They can take the feature space into higher dimensions to solve the problem.
• D.They can be used only for regression.