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What technologies meet the company's requirements?
IT leadership wants Jo transition a company's existing machine learning data storage environment to AWS as a temporary ad hoc solution. The company currently uses a custom software process that heavily leverages SOL as a query language and exclusively stores generated csv documents for machine learning The ideal state for...
Which of the following modeling techniques should the Specialist use1?
A Machine Learning Specialist is building a supervised model that will evaluate customers' satisfaction with their mobile phone service based on recent usage. The model's output should infer whether or not a customer is likely to switch to a competitor in the next 30 days. Which of the following modeling...
Which built-in Amazon SageMaker machine learning algorithm should be used for modeling this problem?
A bank's Machine Learning team is developing an approach for credit card fraud detection. The company has a large dataset of historical data labeled as fraudulent. The goal is to build a model to take the information from new transactions and predict whether each transaction is fraudulent or not Which...
For the given confusion matrix, what is the recall and precision of the model?
For the given confusion matrix, what is the recall and precision of the model? A . Recall = 0.92 Precision = 0.84B . Recall = 0.84 Precision = 0.8C . Recall = 0.92 Precision = 0.8D . Recall = 0.8 Precision = 0.92View AnswerAnswer: C Explanation: Recall and precision are...
Which action is recommended to provide the HIGHEST accuracy model for the company's test and validation data?
A web-based company wants to improve its conversion rate on its landing page Using a large historical dataset of customer visits, the company has repeatedly trained a multi-class deep learning network algorithm on Amazon SageMaker However there is an overfitting problem training data shows 90% accuracy in predictions, while test...
Which compute choice should the Machine Learning Specialist select to train and achieve good accuracy on the model quickly?
An e-commerce company needs a customized training model to classify images of its shirts and pants products. The company needs a proof of concept in 2 to 3 days with good accuracy. Which compute choice should the Machine Learning Specialist select to train and achieve good accuracy on the model...
Which approach should the Specialist use for training a model using that data?
A Machine Learning Specialist has completed a proof of concept for a company using a small data sample and now the Specialist is ready to implement an end-to-end solution in AWS using Amazon SageMaker. The historical training data is stored in Amazon RDS Which approach should the Specialist use for...
Which storage scheme is MOST adapted to this scenario?
A Data Science team is designing a dataset repository where it will store a large amount of training data commonly used in its machine learning models. As Data Scientists may create an arbitrary number of new datasets every day the solution has to scale automatically and be cost-effective. Also, it...
A Machine Learning Specialist is working with a media company to perform classification on popular articles from the company's website. The company is using random forests to classify how popular an article will be before it is published A sample of the data being used is below.
A Machine Learning Specialist is working with a media company to perform classification on popular articles from the company's website. The company is using random forests to classify how popular an article will be before it is published A sample of the data being used is below. Given the dataset,...
Which machine learning approach should be used to solve this problem?
A manufacturing company has a large set of labeled historical sales data. The manufacturer would like to predict how many units of a particular part should be produced each quarter. Which machine learning approach should be used to solve this problem?A . Logistic regressionB . Random Cut Forest (RCF)C ....
