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Interactive Visualization

Interactive visualization is a field of computer science and programming that is focused on graphic visualizations and improving the way we can access and interact with information.

Graphic visualizations also refer to the graphic displays used by analytics and business intelligence tools. Most often, these visualizations form part of interactive dashboards considering they are useful for providing a quick and easy ways to understand insights based on changing data.

What is the purpose of learning data visualization for machine learning?

Data visualization is used to convey information (e.g result or insight from machine learning). You wouldn’t want your finding to ends up with you. Knowing the correct principle of data visualization enables you to convey correct information that is easy to be understood, less explanation needed and does not pain the eye. See the full article for more details.

What is an interactive data analysis?

Interactive data analysis works mostly in a loop fashion. You start with some sort of loosely specified goal, translate the goal into one or more questions, organize and analyze the data to answer these questions, generate new questions and start over.

How is data visualization used?

Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science.

What is data analysis and visualization?

Data visualization is nothing but, representing data in a visual form. Data analytics is the method of examining data sets (structured or unstructured) in order to get useful insights to draw conclusions about the datasets. Data analytics techniques and technologies are widely used in many organizations.

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