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NEW QUESTION: 1
Which virtual storage configuration can be created with Veritas Storage Foundation 6.1 for UNIX?
A. RAID
B. SVM
C. LPAR
D. LVM
Answer: A

NEW QUESTION: 2
You are a data scientist building a deep convolutional neural network (CNN) for image classification.
The CNN model you built shows signs of overfitting.
You need to reduce overfitting and converge the model to an optimal fit.
Which two actions should you perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Add an additional dense layer with 512 input units.
B. Use training data augmentation
C. Add L1/L2 regularization.
D. Reduce the amount of training data.
E. Add an additional dense layer with 64 input units
Answer: C,D
Explanation:
Explanation
References:
https://machinelearningmastery.com/how-to-reduce-overfitting-in-deep-learning-with-weight-regularization/
https://en.wikipedia.org/wiki/Convolutional_neural_network

NEW QUESTION: 3
Azure Machine Learning Studioで分類タスクを実行しています。
提供されたデータセットに基づいて、バランスの取れたテストおよびトレーニングサンプルを準備する必要があります。
0.75：0.25の比率でデータを分割する必要があります。
各パラメーターにどの値を使用する必要がありますか？ 回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation:
Box 1: Split rows
Use the Split Rows option if you just want to divide the data into two parts. You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.
You can also randomize the selection of rows in each group, and use stratified sampling. In stratified sampling, you must select a single column of data for which you want values to be apportioned equally among the two result datasets.
Box 2: 0.75
If you specify a number as a percentage, or if you use a string that contains the "%" character, the value is interpreted as a percentage. All percentage values must be within the range (0, 100), not including the values 0 and 100.
Box 3: Yes
To ensure splits are balanced.
Box 4: No
If you use the option for a stratified split, the output datasets can be further divided by subgroups, by selecting a strata column.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data

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