Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

CHAPTER 1
Introduction
In this book, I assume that you are familiar with Python programming.
In this introductory chapter, I explain why a data scientist should choose
Python as a programming language. Then I highlight some situations
where Python is not a good choice. Finally, I describe some good practices
in application development and give some coding examples that a data
scientist needs in their day-to-day job.
Why Python?
So, why should you choose Python?
• It has versatile libraries. You always have a readymade
library in Python for any kind of application.
From statistical programming to deep learning to
network application to web crawling to embedded
systems, you will always have a ready-made library in
Python. If you learn this language, you do not have to
stick to a specific use case. R has a rich set of analytics
libraries, but if you are working on an Internet of Things
(IoT) application and need to code in a device-side
embedded system, it will be difficult in R.
© Sayan Mukhopadhyay 2018
S. Mukhopadhyay, Advanced Data Analytics Using Python,
https://doi.org/10.1007/978-1-4842-3450-1_1
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