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5 5 Statistical Data
Statistical Data

u Applications of Data Science u Working with CSV Files in Python
u Types of Data u Data Visualisation in Python
u Data Access in Python u Low/No-Code AI for Statistical Data
u Statistical Learning with Python u Orange Data Mining Tool

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, needs data from all the websites under consideration.
APPLICATIONS OF DATA SCIENCE

Data science is not a new field. In your daily life, you have seen a number 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 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 recommendation on Amazon, movie
recommendations on Netflix, and music suggestions on YouTube are some real world applications of the
recommender system which are totally based on data science.

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