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The main difference among these three technical terms are as follows:

Basis Artificial Intelligence Machine Learning Deep Learning
Learning Power AI enables machines to The Machine Deep learning or deep
think without any human Learning systems neural learning is a subset
intervention. can automatically of machine learning
learn and improve techniques. Deep learning
without explicitly being systems are capable of
programmed. learning by example.
Applications The main applications Product recommendation Driverless Cars and
of AI are Siri, customer engine used by various Autonomous vehicles are
support using catboats, e-commerce websites is examples of Deep Learning
Expert System, Online an example of Machine Systems.
game playing, intelligent learning systems.
humanoid robot, etc.
Data Dependencies AI systems give excellent Machine Learning Deep learning systems give
performance on a big systems give excellent excellent performance on a
dataset. performances on a small/ big dataset.
medium dataset
Data Type The data required by AI The data required The data required by Deep
systems can be either by Machine learning Learning systems can
structured, unstructured or systems is mostly in be either structured or
semi-structured. structured form. unstructured because they
rely on the layers of the
Artificial neural network.

Problems/ Tasks AI systems are able to Machine learning models Deep learning models are
perform various complex are suitable for solving suitable for solving complex
problems. simple or bit-complex problems.
problems.
COMMON TERMINOLOGIES USED WITH DATA

Data is indeed the cornerstone of AI models. Without sufficient and reliable data, no AI model can be developed
or implemented, as the quality of data directly influences the performance and reliability of these models.
Let’s learn about data and the common terminologies associated with it.

Data

Data are the raw facts or figures that are collected and stored in various forms. It can represent facts, statistics, or
any other type of information that can be processed or analysed. In the context of computing and data science,
data plays a critical role in building AI models, conducting analyses, and making informed decisions.
For example, a table with information about colours is data, where each row will contain information about
different colours. Each color is described by a RGB code.
Colour Colour Type RGB Code

Red Primary (255, 0, 0)
Green Secondary (0, 255, 0)
Red-Purple Tertiary (80, 0, 255)

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