Question

In what phase does the analyst deal with the following: Creating training and testing datasets to build models from? Identify/detect patterns? Determine if groups (clusters) exist in data? Classify data into groups? Create models that "learn" and improve (e.g., machine/deep learning, AI, etc)

Answer 1

The phase in which the analyst deals with creating training and testing datasets, identifying patterns, determining if groups exist in the data, classifying data into groups, and creating models that learn and improve is called the Modeling phase.

Step-by-step explanation:

In the field of data analysis, the phase in which the analyst deals with creating training and testing datasets, identifying patterns, determining if groups exist in the data, classifying data into groups, and creating models that learn and improve is called the Modeling phase.In this phase, the analyst preprocesses the data to create training and testing datasets. They then use various data mining and machine learning techniques to identify patterns and determine if groups or clusters exist in the data. The analyst also builds models that can classify data into groups and continuously improve through techniques like machine learning and deep learning.Example: In a retail company, an analyst may create training and testing datasets from customer purchase history. They use clustering techniques to group customers based on their buying behavior. Then, they create a machine learning model to predict customer buying preferences.