Suresh A., Malarvizhi N., Raj P., Neeba E.A. Practical Python Programming for Data Scientists

Arcler Press, 2022. — 346 p. — ISBN: 978-1-77469-337-7.Data Science plays a very vital role in shaping the process of transitioning data into information and knowledge. As business enterprises, organizations, governments, IT companies, and service providers are keenly becoming data-driven, the role and responsibility of data scientists are bound to go up significantly. Python is emerging as the leading programming language for Data Science projects. The book aims to clearly explain how Python simplifies and speeds up the realization of next-generation Data Science applications.Data Science (DS) is a fast-emerging field of study and research. It leverages integrated data analytics (big, fast, and streaming analytics) platforms and Artificial Intelligence (AI) (machine and deep learning (ML/DL), computer vision (CV), and natural language processing (NLP)) algorithms extensively to extract actionable insights out of burgeoning data volumes in time.Due to the ready availability of several libraries for facilitating the development of data science services, Python is turning out the programming language of choice for data science. The following libraries are enabling data science applications and are made available in Python:NumPy: This is a library that makes a variety of mathematical and statistical operations easier and faster. This is also the basis for many features of the Pandas library.Pandas: Pandas is a fast, powerful, flexible, and easy-to-use open-source data analysis and manipulation tool, built on top of the Python programming language. This is one of the game changers for the tremendous success of data science projects.Matplotlib: This is a visualization library that makes it quick and easy to generate charts from data.
Scikit-Learn: This is the most popular library for machine learning (ML) work in Python.The Distinctions of Python Language.
Demystifying the Data Science Paradigm.
Python for Data Analysis.
Python Programming: An Introduction.
Functions.
Control Structures.
Strings.
Lists.
Tuples.
Dictionaries.
Files.
Modules and Packages.
Classes in Python.