Which of the following describes transfer learning in the context of machine learning?

• Using a previous model as the basis for a new model

• Using a data pipeline to transfer training data to the machine

• Reducing model performance to decrease training time

• Deploying a model in cloud services so many users can benefit from it

Which type of machine learning are you performing if you provide labels as you train the model?

• Supervised

• Clustering

• Unsupervised

• Dimensionality reduction

Which of the following 'Vs' of big data underscores the importance of considering unstructured sources of data in solving business problems?

• Variety

• Velocity

• Veracity

• Volume

Which of the following scenarios demonstrates concept drift in machine learning models?

• A specific model that predicts housing prices is no longer effective due to significant changes in the housing market over time

• The idea for a model that classifies images is no longer valuable to the organization due to changing business strategies and needs

• A product recommender system currently under development needs to be redesigned due to the emergence of new and improved machine learning algorithms

• The application of a credit card fraud detection model is found to no longer be socially acceptable due to changes in cultural attitudes

What does it mean for a machine learning model to be 'stochastic'?

• The same input can produce different outputs over multiple training sessions

• The outcome of a model does not demonstrate a clear and consistent pattern

• The time and performance requirements of training are the same across multiple sessions

• The model selects a machine learning algorithm at random to use in training

You have a dataset of customer information, such as a customer's location, spending habits, product reviews, and so forth. While you don't have anything specific to predict, you want to engage in customer segmentation so that customers with similarities are considered a unified audience in your targeted marketing campaigns. Which type of machine learning outcome is most appropriate for this situation?

• Clustering

• Classification

• Regression

• Dimensionality reduction

Which of the following describes the relationship between a machine learning model and a machine learning algorithm?

• A machine learning model is created by applying a machine learning algorithm to input data

• A machine learning model is the sum of multiple machine learning algorithms

• A machine learning model represents the input data before it is fed into a machine learning algorithm

• A machine learning model generates a machine learning algorithm through training

Which of the following concepts refers to actionable intelligence?

• Knowledge

• Information

• Wisdom

• Data

You need to load a data file in Python so you can manipulate the columns and rows of data it contains. Which of these tools would enable you to do this?

• Pandas

• Matplotlib

• TensorFlow

• Seaborn

Which software library primarily implements machine learning algorithms?

• Scikit-learn

• Seaborn

• Matplotlib

• SciPy