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4 4 Data Science
Data Science

u Applications of Data Science u Statistical Learning With Python
u AI Project Cycle u Data Visualization in Python
u Types of Data u Classification Model
u Data Access in Python

The term ‘Data Science’ was coined at the beginning of the 21st century. It is attributed to William S. The scientists
or researchers of data science combine statistical and machine learning techniques with Python programming
to analyse and interpret complex data. In the previous chapter, you have learnt that data is the core of artificial
intelligent machines as no AI system can be developed or functional without adequate data. For example, a
comparison shopping website where customers can use filters and compare products on the basis of price,
features, reviews and other criteria.
APPLICATIONS OF DATA SCIENCE

As you know, data science is not a new field. The adequate amount of data is required to develop a machine
which is intelligent artificially. In your daily life, you have seen a lot of AI applications which are based on data,
or images. Let’s explore this section to know more about the applications of data science.

u Fraud Detection: Nowadays, the banking industry
uses AI technology based on data that allows users to
deposit cheque or cash and can do a multiple number
of transactions without leaving homes. In the financial
industry, data science is used to detect anomalies and
frauds.

u Product Recommendation Engine: The product recommendation engine, also known as information filtering
system are available that collects data from your profile and offer you exact information that you’re interested
in based on your behaviour and taste. Product recommendations on Amazon, movie recommendations on
Netflix, music suggestions on YouTube are some real world applications of the recommender system which
are totally based on data science.

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