Book Image

Python for Geeks

By : Muhammad Asif
Book Image

Python for Geeks

By: Muhammad Asif

Overview of this book

Python is a multipurpose language that can be used for multiple use cases. Python for Geeks will teach you how to advance in your career with the help of expert tips and tricks. You'll start by exploring the different ways of using Python optimally, both from the design and implementation point of view. Next, you'll understand the life cycle of a large-scale Python project. As you advance, you'll focus on different ways of creating an elegant design by modularizing a Python project and learn best practices and design patterns for using Python. You'll also discover how to scale out Python beyond a single thread and how to implement multiprocessing and multithreading in Python. In addition to this, you'll understand how you can not only use Python to deploy on a single machine but also use clusters in private as well as in public cloud computing environments. You'll then explore data processing techniques, focus on reusable, scalable data pipelines, and learn how to use these advanced techniques for network automation, serverless functions, and machine learning. Finally, you'll focus on strategizing web development design using the techniques and best practices covered in the book. By the end of this Python book, you'll be able to do some serious Python programming for large-scale complex projects.
Table of Contents (20 chapters)
1
Section 1: Python, beyond the Basics
5
Section 2: Advanced Programming Concepts
9
Section 3: Scaling beyond a Single Thread
13
Section 4: Using Python for Web, Cloud, and Network Use Cases

Using Python for machine learning

Python is a popular language in the data scientist community because of its simplicity, cross-platform compatibilities, and rich support for data analysis and data processing through its libraries. One of the key steps in machine learning is preparing data for building the ML models, and Python is a natural winner in doing this. The only challenge in using Python is that it is an interpreted language, so the speed of executing code is slow in comparison to languages such as C. But this is not a major issue as there are libraries available to maximize Python's speed by using multiple cores of central processing units (CPUs) or graphics processing units (GPUs) in parallel.  

In the next subsection, we will introduce a few Python libraries for machine learning.

Introducing machine learning libraries in Python

Python comes with several machine learning libraries. We already mentioned supporting libraries such as NumPy, SciPy, and...