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NEW QUESTION: 1
You create a multi-class image classification deep learning experiment by using the PyTorch framework. You plan to run the experiment on an Azure Compute cluster that has nodes with GPU's.
You need to define an Azure Machine Learning service pipeline to perform the monthly retraining of the image classification model. The pipeline must run with minimal cost and minimize the time required to train the model.
Which three pipeline steps should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:
Explanation:

Explanation:
Step 1: Configure a DataTransferStep() to fetch new image data...
Step 2: Configure a PythonScriptStep() to run image_resize.y on the cpu-compute compute target.
Step 3: Configure the EstimatorStep() to run training script on the gpu_compute computer target.
The PyTorch estimator provides a simple way of launching a PyTorch training job on a compute target.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-pytorch

NEW QUESTION: 2
MySQL Enterprise Masking and De-identification can hide or obfuscate sensitive data, by controlling how the data appears. Which three are MySQL Enterprise Masking and De-identification functions?
A. dictionary substitution
B. whitelisting and substitution
C. misspelling
D. strict or relaxed masking
E. random data substitution
Answer: A,D,E
Explanation:
Robust Data Masking Functions
MySQL Enterprise Masking and De-identification can hide or obfuscate sensitive data, by controlling how the data appears. It features robust masking algorithms including selective masking, blurring, random data substitution and other special techniques for credit card numbers, account numbers and other personally identifiable information, enabling IT departments to maintain structural rules to de-identify values. MySQL Enterprise Masking and De-identification functions include:
* Selective Masking - Obscures a particular portion of numbers or strings such as phone numbers, and payment card numbers.
* Strict or Relaxed Masking - Implement strict or relaxed masking to obfuscate data.
* Random Data Substitution - Replace real values with random values while maintaining format consistency.
* Blurring - Add a random variance to existing values such as randomized numeric ranges for salaries.
* Dictionary Substitution - Randomly replace values from task specific dictionaries.
* Blacklisting and Substitution - Replace specifically blacklisted data, but leave non-blacklisted in place.
https://www.mysql.com/products/enterprise/masking.html#:~:text=Robust%20Data%20Masking%20Functions,controlling%20how%20the%20data%20appears.&text=Random%20Data%20Substitution%20%2D%20Replace%20real,values%20while%20maintaining%20format%20consistency.

NEW QUESTION: 3
What are the advantages of a merge join versus a hash join? (Select two.)
A. A merge join uses memory more efficiently.
B. Sometimes a merge join runs faster than a hash join.
C. A merge join can spill to disk if the inner table is too large.
D. A merge join joins the data into a new projection.
E. A merge join requires no optimization.
Answer: B,D

NEW QUESTION: 4
What statement describes what DNS64 does?
A. Synthesizes DNS AAAA records from A records.
B. Translates the destination IPv4 address of the DNS traffic to an IPv6 address.
C. Translates the destination IPv6 address of the DNS traffic to an IPv4 address.
D. Converts DNS A record lookups to AAAA record lookups.
Answer: C