APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNING PIPELINE
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Use Amazon SageMaker hosting services and specify a single instance. Use Route53 with failover routing policy to ensure users are routed to different availability zone if the instance becomes unreachable
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Use Amazon SageMaker hosting services, deploy two different variants of the model routing 50% of the traffic to one availability zone and the other 50% to the other availability zone
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Use Amazon SageMaker hosting services, specify two or more instances and specify multiple availability zones you want to launch models in
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Use Amazon SageMaker hosting services and specify two or more instances. Amazon SageMaker launches them in multiple availability zones automatically
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Detailed explanation-1: -Overfitting describes the phenomenon where a machine learning model (typically a neural network) is so complex and intricate that it can account for all possible cases, but fails to generalize its predictions to unseen data points.
Detailed explanation-2: -In summary, more data is always better-one should try and collect it provided the cost of data acquisition is not too high. Better algorithms (in a statistical or theoretical sense) is not always better if it cannot be used.
Detailed explanation-3: -Performance. The quality of the model’s results is a fundamental factor to take into account when choosing a model. Explainability. Complexity. Dataset size. Dimensionality. Training time and cost. Inference time. Conclusions. 13-Jul-2021