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NEW QUESTION: 1
What is the purpose of L1 interfaces and L2 interfaces on Cisco UCS Series Fabric Interconnects?
A. To provide path redundancy if the Ethernet uplink fails
B. To provide cluster control capability between the Fabric Interconnects
C. L1 is used to provide management connectivity, while the L2 interfaces in each Fabric Interconnect connect directly to achieve clustering
D. L2 is used to provide management connectivity, while the L1 interfaces in each Fabric Interconnect connect directly to achieve clustering
Answer: B
NEW QUESTION: 2
You have recently joined a startup company building sensors to measure street noise and air quality in urban areas.
The company has been running a pilot deployment of around 100 sensors for 3 months Each sensor uploads 1KB of sensor data every minute to a backend hosted on AWS.
During the pilot, you measured a peak or 10 IOPS on the database, and you stored an average of 3GB of sensor data per month in the database
The current deployment consists of a load-balanced auto scaled Ingestion layer using EC2 instances and a PostgreSQL RDS database with 500GB standard storage.
The pilot is considered a success and your CEO has managed to get the attention or some potential investors
The business plan requires a deployment of at least 1O0K sensors which needs to be supported by the backend
You also need to store sensor data for at least two years to be able to compare year over year Improvements.
To secure funding, you have to make sure that the platform meets these requirements and leaves room for further scaling
Which setup win meet the requirements?
A. Ingest data into a DynamoDB table and move old data to a Redshift cluster
B. Add an SOS queue to the ingestion layer to buffer writes to the RDS instance
C. Keep the current architecture but upgrade RDS storage to 3TB and 10K provisioned IOPS
D. Replace the RDS instance with a 6 node Redshift cluster with 96TB of storage
Answer: D
NEW QUESTION: 3
群衆感情モデルの評価戦略を定義する必要があります。
順番に実行する必要がある3つのアクションはどれですか?回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。
Answer:
Explanation:
Explanation
Step 1: Define a cross-entropy function activation
When using a neural network to perform classification and prediction, it is usually better to use cross-entropy error than classification error, and somewhat better to use cross-entropy error than mean squared error to evaluate the quality of the neural network.
Step 2: Add cost functions for each target state.
Step 3: Evaluated the distance error metric.
References:
https://www.analyticsvidhya.com/blog/2018/04/fundamentals-deep-learning-regularization-techniques/