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

Introducing machine learning

In traditional programming, we provide data and some rules as input to our program to get the desired output. Machine learning is a fundamentally different programming approach, in which the data and the expected output are provided as input to produce a set of rules. This is called a model in machine learning nomenclature. This concept is illustrated in the following diagram:

Figure 13.1 – Traditional programming versus machine learning programming

To understand how machine learning works, we need to familiarize ourselves with its core components or elements:

  • Dataset: Without a good set of data, machine learning is nothing. Good data is the real power of machine learning. It has to be collected from different environments and cover various situations to represent a model close to a real-world process or system. Another requirement for data is that it has to be large, and by large we mean thousands of records. Moreover...