Book Image

Learn Python by Building Data Science Applications

By : Philipp Kats, David Katz
Book Image

Learn Python by Building Data Science Applications

By: Philipp Kats, David Katz

Overview of this book

Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.
Table of Contents (26 chapters)
Free Chapter
1
Section 1: Getting Started with Python
11
Section 2: Hands-On with Data
17
Section 3: Moving to Production

Chapter 9

What is a shell? Why and when are command-line interfaces advantageous compared to graphical interfaces?

A shell is a user interface that you use to interact with the operating system of a computer. Usually, people use this term to refer to a command-line shell that allows you to control the OS with a set of textual commands. There are three main advantages of command-line interfaces over GUIs. First, textual commands can be combined and stored and thus form scripts. Second, they require a minimal amount of memory and thus are way more suitable for interacting with remote machines via the internet. Third, command-line interfaces are quite unified across different operating systems—commands on Linux and macOS are identical, and even Windows has either similar or aliased commands.

What exactly does version control mean? Is it suitable for research projects?

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