COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Online inference
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Batch inference
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Either A or B
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None of the above
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Detailed explanation-1: -If predictions need to served on an individual basis and within the time of a single web request, online inference is the way to go.
Detailed explanation-2: -offline inference, meaning that you make all possible predictions in a batch, using a MapReduce or something similar. You then write the predictions to an SSTable or Bigtable, and then feed these to a cache/lookup table. online inference, meaning that you predict on demand, using a server.
Detailed explanation-3: -What is Latency in Machine Learning (ML)? Latency is a measurement in Machine Learning to determine the performance of various models for a specific application. Latency refers to the time taken to process one unit of data provided only one unit of data is processed at a time.
Detailed explanation-4: -Batch inference: An asynchronous process that bases its predictions on a batch of observations. The predictions are stored as files or in a database for end users or business applications. Real-time (or interactive) inference: Frees the model to make predictions at any time and trigger an immediate response.
Detailed explanation-5: -Dynamic (online) inference means making predictions on demand. That is, in online inference, we put the trained model on a server and issue inference requests as needed.