A company wants to build an anomaly detection ML model. The model will use large-scale tabulardata that is stored in an Amazon S3 bucket. The company does not have expertise in Python, Spark,or other languages for ML.An ML engineer needs to transform and prepare the data for ML model training.Which solution will meet these requirements?
A travel company has trained hundreds of geographic data models to answer customer questions byusing Amazon SageMaker AI. Each model uses its own inferencing endpoint, which has become anoperational challenge for the company.The company wants to consolidate the models' inferencing endpoints to reduce operationaloverhead.Which solution will meet these requirements?
An ML engineer is setting up an Amazon SageMaker AI pipeline for an ML model. The pipeline mustautomatically initiate a re-training job if any data drift is detected.How should the ML engineer set up the pipeline to meet this requirement?
A government agency is conducting a national census to assess program needs by area and city. Thecensus form collects approximately 500 responses from each citizen. The agency needs to analyzethe data to extract meaningful insights. The agency wants to reduce the dimensions of the highdimensionaldata to uncover hidden patterns.Which solution will meet these requirements?
An ML engineer has trained a neural network by using stochastic gradient descent (SGD). The neuralnetwork performs poorly on the test set. The values for training loss and validation loss remain highand show an oscillating pattern. The values decrease for a few epochs and then increase for a fewepochs before repeating the same cycle.What should the ML engineer do to improve the training process?