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Numeric data can be further classified as:
Continuous Data Discrete Data
Continuous data can take any numeric value within a Discrete data refers to distinct single values. It
specified range. consists of whole numbers without decimal parts
that represent distinct categories or values.
Continuous data is measurable. Discrete data is countable.
This type of data can be infinitely subdivided and Discrete data cannot be subdivided meaningfully.
often includes decimal points.
Often used to analyse using statistical techniques It is used to analyse using frequency distributions,
such as mean, median, standard deviation, and bar charts, and probability distributions.
correlation.
Examples: dimensions of classroom, height, weight, Examples: number of girls and boys in class, number
temperature, time, etc. of subjects in class 9th, count of anything.
Qualitative Data versus Quantitative Data
Quantitative Data Qualitative Data
Data is depicted in numerical terms. Data is not depicted in numerical terms.
Can be shown in numbers and variables like ratio, Could be about the behavioural attributes of a
percentage, and more. person, or things.
Examples: 100%, 1:3, 123 Examples: loud behaviour, fair skin, soft quality, and
more.
AI Domains and Type of Data
Various types of data are utilised across different domains to train models, make predictions, and generate
insights. Here are the types of data commonly used in three key domains of AI:
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a field of Computer Science and a subfield of Artificial Intelligence that aims
to make computers understand human language. It's all about teaching, and training computers to understand
and work with human language. Types of data used in NLP are:
● Textual data: This includes a wide range of written text, such as articles, books, emails, social media posts,
web content, PDF files, etc.
● Audio data: Audio recordings of spoken language, which are transcribed into textual data.
Computer Vision
Computer Vision is a field of Artificial Intelligence (AI) that uses machine learning and neural networks to teach
computers to derive meaningful information from digital images, videos and other visual inputs. It is like giving
eyes to computers. It helps them look at pictures and videos from the real world and understand what they’re
seeing. With Computer Vision, computers can figure out what’s in a picture or video, just like we do. They can
recognise objects, people, and even actions happening in videos.
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