Feature Table inML Modelling — Learn free

Self-check

Questions 1–10 of 10

1. In machine learning modelling, what is a Feature?
Question 1A. A new table created and populated from raw data using data wrangling, used as the source for an ML modelB. A button in a dashboard that runs a modelC. The algorithm that a data scientist choosesD. The prediction produced by a modelE. A licence option in a data science tool
2. How does I Am Datapedia! summarise what a Feature is in its key phrase?
Question 2A. A Feature is a trained modelB. A Feature is a data scientist's hypothesisC. A Feature is nothing more than a traditional tableD. A Feature is a chart of raw dataE. A Feature is an unstructured document
3. Why do data scientists need raw but relevant data rather than all raw data?
Question 3A. Because raw data is always encryptedB. Because ML models cannot read tablesC. Because raw data is stored only on paperD. Because raw data must be deleted after useE. Because raw data includes irrelevant data, and training a model does not need all of it
4. Who ideally cleans and filters the data before it is fed into a machine learning model?
Question 4A. The end customersB. Data engineers, or the data scientists themselvesC. The database vendorD. The marketing departmentE. The model itself
5. A global table holds one million customer rows, but a model must predict buying behaviour for one country and one set of products. What is created?
Question 5A. A copy of the full one million rowsB. A random sample of one hundred rowsC. A second model for every other countryD. A new table holding only that country's data for the required products, used as the model's sourceE. A summary report for management
6. Which process is used to populate a Feature table from raw data?
Question 6A. Data EncryptionB. Data ArchivingC. Data WranglingD. Data MonetisationE. Data Splitting
7. How is Data Science described in the discussion of Feature tables?
Question 7A. Running algorithms and machine learning models on structured, semi-structured and unstructured datasets for analyticsB. Designing relational databases for transactionsC. Writing reports for senior managementD. Backing up data to the cloudE. Managing user access to data
8. Which statement about a Feature table is NOT correct?
Question 8A. It is a table created from raw dataB. It is used as the source for a machine learning modelC. It is populated using data wranglingD. It holds only the relevant raw dataE. It must contain all of the raw data available
9. According to I Am Datapedia!, which group might not be aware of the term Feature as used in Data Science?
Question 9A. Data engineersB. Non-data scientists and non-data citizensC. Machine learning researchersD. Database designersE. ETL developers
10. What is described as the basic requirement of any machine learning model?
Question 10A. A cloud subscriptionB. A graphical user interfaceC. A dedicated data scientist per modelD. DataE. A relational database licence