You are analyzing a numerical dataset which contains missing values in several columns. You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set. You need to analyze a full dataset to include all values. Solution: Remove the entire column that contains the missing data point. Does the […]

You are analyzing a numerical dataset which contains missing values in several columns. You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set. You need to analyze a full dataset to include all values. Solution: Replace each missing value using the Multiple Imputation by Chained Equations (MICE) […]

You plan to deliver a hands-on workshop to several students. The workshop will focus on creating data visualizations using Python. Each student will use a device that has internet access. Student devices are not configured for Python development. Students do not have administrator access to install software on their devices. Azure subscriptions are not available […]

Case study Overview You are a data scientist in a company that provides data science for professional sporting events. Models will use global and local market data to meet the following business goals: • Understand sentiment of mobile device users at sporting events based on audio from crowd reactions. • Assess a user’s tendency to […]

You are moving a large dataset from Azure Machine Learning Studio to a Weka environment. You need to format the data for the Weka environment. Which module should you use? A. Convert to CSV B. Convert to Dataset C. Convert to ARFF D. Convert to SVMLight Explanation: Use the Convert to ARFF module in Azure […]

You must store data in Azure Blob Storage to support Azure Machine Learning. You need to transfer the data into Azure Blob Storage. What are three possible ways to achieve the goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point. A. Bulk Insert SQL Query B. AzCopy C. […]

You are developing deep learning models to analyze semi-structured, unstructured, and structured data types. You have the following data available for model building: • Video recordings of sporting events • Transcripts of radio commentary about events • Logs from related social media feeds captured during sporting events You need to select an environment for creating […]

You are implementing a machine learning model to predict stock prices. The model uses a PostgreSQL database and requires GPU processing. You need to create a virtual machine that is pre-configured with the required tools. What should you do? A. Create a Data Science Virtual Machine (DSVM) Windows edition. B. Create a Geo Al Data […]

You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size. You have the following requirements: • Models must be built using Caffe2 or Chainer frameworks. • Data scientists must be able to use a data science environment to build the machine […]

Your team is building a data engineering and data science development environment. The environment must support the following requirements: • support Python and Scala • compose data storage, movement, and processing services into automated data pipelines • the same tool should be used for the orchestration of both data engineering and data science • support […]