A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using AmazonSageMaker with Area Under the ROC Curve (AUC) as the objective metric. This workflow will eventually be deployed in apipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours.With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialistwants to reconfigure the input hyp

A real-estate company is launching a new product that predicts the prices of new houses. The historical data for theproperties and prices is stored in .csv format in an Amazon S3 bucket. The data has a header, some categorical fields, andsome missing values. The companys data scientists have used Python with a common open-source library to fill the missingvalues with zeros. The data scientists have dropped all of the categorical fields and have trained a model by using the open-source linear regression algo

A data scientist is training a text classification model by using the Amazon SageMaker built-in BlazingText algorithm. Thereare 5 classes in the dataset, with 300 samples for category A, 292 samples for category B, 240 samples for category C, 258samples for category D, and 310 samples for category E.The data scientist shuffles the data and splits off 10% for testing. After training the model, the data scientist generatesconfusion matrices for the training and test sets.What could the data scientist conclude

An Machine Learning Specialist discover the following statistics while experimenting on a model. What can the Specialist from the experiments?

A company wants to predict the sale prices of houses based on available historical sales data. The target variable in thecompanys dataset is the sale price. The features include parameters such as the lot size, living area measurements, non-living area measurements, number of bedrooms, number of bathrooms, year built, and postal code. The company wants touse multi-variable linear regression to predict house sale prices.Which step should a machine learning specialist take to remove features that are irreleva

A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine LearningSpecialist would like to build a binary classifier based on two features: age of account and transaction month. The classdistribution for these features is illustrated in the figure provided.Based on this information, which model would have the HIGHEST recall with respect to the fraudulent class?

A manufacturing company uses machine learning (ML) models to detect quality issues. The models use images that aretaken of the company's product at the end of each production step. The company has thousands of machines at theproduction site that generate one image per second on average.The company ran a successful pilot with a single manufacturing machine. For the pilot, ML specialists used an industrial PCthat ran AWS IoT Greengrass with a long-running AWS Lambda function that uploaded the images to Amazon

A Machine Learning Specialist built an image classification deep learning model. However the Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and 75%r respectively. How should the Specialist address this issue and what is the reason behind it?

A retail company is selling products through a global online marketplace. The company wants to use machine learning (ML)to analyze customer feedback and identify specific areas for improvement. A developer has built a tool that collects customerreviews from the online marketplace and stores them in an Amazon S3 bucket. This process yields a dataset of 40 reviews.A data scientist building the ML models must identify additional sources of data to increase the size of the dataset.Which data sources should the

A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data. The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format without data loss. The output datastore must be highly available, and Analysts must be able to run SQL queries against the data and connect to existing business intelligence dashboards. Which solution should the Data Scientist build to satisfy the requirements?

A Data Scientist is developing a binary classifier to predict whether a patient has a particular disease on a series of testresults. The Data Scientist has data on 400 patients randomly selected from the population. The disease is seen in 3% of thepopulation.Which cross-validation strategy should the Data Scientist adopt?

A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training. The dataset is stored in Amazon S3 and contains Personally Identifiable Information (Pll). The dataset: * Must be accessible from a VPC only. * Must not traverse the public internet. How can these requirements be satisfied?

During mini-batch training of a neural network for a classification problem, a Data Scientist notices that training accuracy oscillates What is the MOST likely cause of this issue?

A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a machine learningspecialist will build a binary classifier based on two features: age of account, denoted by x, and transaction month, denotedby y. The class distributions are illustrated in the provided figure. The positive class is portrayed in red, while the negativeclass is portrayed in black.Which model would have the HIGHEST accuracy?

A Machine Learning Specialist must build out a process to query a dataset on Amazon S3 using Amazon Athena. Thedataset contains more than 800,000 records stored as plaintext CSV files. Each record contains 200 columns and isapproximately 1.5 MB in size. Most queries will span 5 to 10 columns only.How should the Machine Learning Specialist transform the dataset to minimize query runtime?

A city wants to monitor its air quality to address the consequences of air pollution A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city As this is a prototype, only daily data from the last year is available Which model is MOST likely to provide the best results in Amazon SageMaker?

A gaming company has launched an online game where people can start playing for free, but they need to pay if theychoose to use certain features. The company needs to build an automated system to predict whether or not a new user willbecome a paid user within 1 year. The company has gathered a labeled dataset from 1 million users.The training dataset consists of 1,000 positive samples (from users who ended up paying within 1 year) and 999,000negative samples (from users who did not use any paid features). E

A Machine Learning Specialist is assigned a TensorFlow project using Amazon SageMaker for training, and needs to continue working for an extended period with no Wi-Fi access. Which approach should the Specialist use to continue working?

A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions Here is an example from the dataset "The quck BROWN FOX jumps over the lazy dog " Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Select THREE)

A Machine Learning Specialist is deciding between building a naive Bayesian model or a full Bayesian network for aclassification problem. The Specialist computes the Pearson correlation coefficients between each feature and finds thattheir absolute values range between 0.1 to 0.95.Which model describes the underlying data in this situation?

A company wants to enhance audits for its machine learning (ML) systems. The auditing system must be able to perform metadata analysis on the features that the ML models use. The audit solution must generate a report that analyzes the metadata. The solution also must be able to set the data sensitivity and authorship of features. Which solution will meet these requirements with the LEAST development effort? The solution that will meet the requirements with the least development effort is to use Amazon SageM

When submitting Amazon SageMaker training jobs using one of the built-in algorithms, which common parameters MUST bespecified? (Choose three.)

A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data.The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format withoutdata loss. The output datastore must be highly available, and Analysts must be able to run SQL queries against the data andconnect to existing business intelligence dashboards.Which solution should the Data Scientist build to satisfy the requirements?

A machine learning specialist stores IoT soil sensor data in Amazon DynamoDB table and stores weather event data asJSON files in Amazon S3. The dataset in DynamoDB is 10 GB in size and the dataset in Amazon S3 is 5 GB in size. Thespecialist wants to train a model on this data to help predict soil moisture levels as a function of weather events usingAmazon SageMaker.Which solution will accomplish the necessary transformation to train the Amazon SageMaker model with the LEAST amountof administrative overhead?

A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input h