The correct answer is: D. Model Building
Data Science is a process that involves extracting knowledge and insights from data. It is a multidisciplinary field that combines statistics, computer science, and machine learning. The data science process can be divided into the following steps:
- Data Collection
The first step in the data science process is to collect data. This data can be collected from a variety of sources, such as surveys, interviews, experiments, and observational studies.
- Data Cleaning
The next step is to clean the data. This involves removing any errors or inconsistencies in the data.
- Data Analysis
The third step is to analyze the data. This involves using statistical methods to identify patterns and trends in the data.
- Model Building
The fourth step is to build a model. This involves using machine learning algorithms to create a model that can predict future outcomes.
- Model Evaluation
The fifth step is to evaluate the model. This involves testing the model to see how well it performs on unseen data.
- Model Deployment
The sixth step is to deploy the model. This involves making the model available to users so that they can use it to make decisions.
- Model Monitoring
The seventh and final step is to monitor the model. This involves tracking the performance of the model over time and making changes as needed.
In the question, the step that involves building and training predictive models is Model Building.