Python 3 Object-oriented Programming. Building robust and maintainable software with object oriented design patterns in Python

Dusty Phillips

Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's clear, concise syntax.Object-oriented programming is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Many modern programming languages utilize the powerful concepts behind object-oriented programming and Python is no exception.Starting with a detailed analysis of object-oriented analysis and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This book fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software.You'll get an in-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique style. This book will not just teach Python syntax, but will also build your confidence in how to program.You will also learn how to create maintainable applications by studying higher level design patterns. Following this, you'll learn the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems will be introduced in the book. After you discover the joy of unit testing and just how easy it can be, you'll study higher level libraries such as database connectors and GUI toolkits and learn how they uniquely apply object-oriented principles. You'll learn how these principles will allow you to make greater use of key members of the Python eco-system such as Django and Kivy.This new edition includes all the topics that made Python 3 Object-oriented Programming an instant Packt classic. It's also packed with updated content to reflect recent changes in the core Python library and covers modern third-party packages that were not available on the Python 3 platform when the book was first published. 

The Machine Learning Workshop. Get ready to develop your own high-performance machine learning algorithms with scikit-learn - Second Edition

Hyatt Saleh

Machine learning algorithms are an integral part of almost all modern applications. To make the learning process faster and more accurate, you need a tool flexible and powerful enough to help you build machine learning algorithms quickly and easily. With The Machine Learning Workshop, you'll master the scikit-learn library and become proficient in developing clever machine learning algorithms.The Machine Learning Workshop begins by demonstrating how unsupervised and supervised learning algorithms work by analyzing a real-world dataset of wholesale customers. Once you've got to grips with the basics, you'll develop an artificial neural network using scikit-learn and then improve its performance by fine-tuning hyperparameters. Towards the end of the workshop, you'll study the dataset of a bank's marketing activities and build machine learning models that can list clients who are likely to subscribe to a term deposit. You'll also learn how to compare these models and select the optimal one.By the end of The Machine Learning Workshop, you'll not only have learned the difference between supervised and unsupervised models and their applications in the real world, but you'll also have developed the skills required to get started with programming your very own machine learning algorithms.

Graph Data Science with Neo4j. Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project

Estelle Scifo

Neo4j, along with its Graph Data Science (GDS) library, is a complete solution to store, query, and analyze graph data. As graph databases are getting more popular among developers, data scientists are likely to face such databases in their career, making it an indispensable skill to work with graph algorithms for extracting context information and improving the overall model prediction performance.Data scientists working with Python will be able to put their knowledge to work with this practical guide to Neo4j and the GDS library that offers step-by-step explanations of essential concepts and practical instructions for implementing data science techniques on graph data using the latest Neo4j version 5 and its associated libraries. You’ll start by querying Neo4j with Cypher and learn how to characterize graph datasets. As you get the hang of running graph algorithms on graph data stored into Neo4j, you’ll understand the new and advanced capabilities of the GDS library that enable you to make predictions and write data science pipelines. Using the newly released GDSL Python driver, you’ll be able to integrate graph algorithms into your ML pipeline.By the end of this book, you’ll be able to take advantage of the relationships in your dataset to improve your current model and make other types of elaborate predictions.

Machine Learning Engineering with Python. Manage the production life cycle of machine learning models using MLOps with practical examples

Andrew McMahon

Machine learning engineering is a thriving discipline at the interface of software development and machine learning. This book will help developers working with machine learning and Python to put their knowledge to work and create high-quality machine learning products and services.Machine Learning Engineering with Python takes a hands-on approach to help you get to grips with essential technical concepts, implementation patterns, and development methodologies to have you up and running in no time. You'll begin by understanding key steps of the machine learning development life cycle before moving on to practical illustrations and getting to grips with building and deploying robust machine learning solutions. As you advance, you'll explore how to create your own toolsets for training and deployment across all your projects in a consistent way. The book will also help you get hands-on with deployment architectures and discover methods for scaling up your solutions while building a solid understanding of how to use cloud-based tools effectively. Finally, you'll work through examples to help you solve typical business problems.By the end of this book, you'll be able to build end-to-end machine learning services using a variety of techniques and design your own processes for consistently performant machine learning engineering.

Microsoft Windows Intune 2.0: Quickstart Administration. Manage your PCs in the Enterprise through the Cloud with Microsoft Windows Intune book and

David Overton

Microsoft Windows Intune is a cloud service solution that simplifies how small and mid-sized businesses manage and secure PCs using Microsoft cloud services and Windows 7óso your computers and users can operate at peak performance all the time.This step-by-step guide will show you how to plan, set up and maintain Windows Intune, showing you how to manage a group of PCs (either 1 business or several if a partner) from the base operating system, through to the patches, anti-malware solution and deployed software and policies from a central console, using the Windows Intune service. This book takes you through all the steps to plan, set up and maintain Windows Intune and how to manage a group of PCs. The book starts by providing an overview of Cloud Computing and PC Management. The book then dives into topics such as Windows Intune features, signing up for Windows Intune and installing the client software, configuring Windows Intune, proactive management, and monitoring and dealing with alerts, including remote assistance amongst others. As Windows 7 is part of Windows Intune, the book will also cover the minimum steps required to move from Windows XP to Windows 7 while keeping user settings and preferences.

Node.js Cookbook. Practical recipes for building server-side web applications with Node.js 22 - Fifth Edition

Bethany Griggs, Manuel Spigolon

Node.js is a game-changing technology for building modern web applications and tooling, bringing the power of JavaScript to the server and enabling full-stack development in a unified language. This updated edition of this Node.js cookbook, featuring Node.js 22, equips you with the latest advancements and enhancements in the Node.js framework ecosystem.From Bethany Griggs, who has served on the Node.js Technical Steering Committee and participated in the Node.js Release Working Group, and Manuel Spigolon, a core maintainer of Fastify, comes this fifth edition of the Node.js Cookbook to help you master Node.js 22. This book guides you step by step through crafting reusable code with Node.js modules, streamlining development using the Fastify web framework, and implementing data persistence in databases and rigorous testing practices for robust applications. You’ll address security concerns, optimize performance with worker threads, deploy Node.js microservices using containerization and orchestration, and tackle troubleshooting with effective debugging strategies. Packed with real-world examples, this guide empowers you to harness Node.js 22's full potential for creating secure, performant, and dynamic applications.

Build Your Own Programming Language. A programmer's guide to designing compilers, interpreters, and DSLs for solving modern computing problems

Clinton L. Jeffery

The need for different types of computer languages is growing rapidly and developers prefer creating domain-specific languages for solving specific application domain problems. Building your own programming language has its advantages. It can be your antidote to the ever-increasing size and complexity of software.In this book, you’ll start with implementing the frontend of a compiler for your language, including a lexical analyzer and parser. The book covers a series of traversals of syntax trees, culminating with code generation for a bytecode virtual machine. Moving ahead, you’ll learn how domain-specific language features are often best represented by operators and functions that are built into the language, rather than library functions. We’ll conclude with how to implement garbage collection, including reference counting and mark-and-sweep garbage collection. Throughout the book, Dr. Jeffery weaves in his experience of building the Unicon programming language to give better context to the concepts where relevant examples are provided in both Unicon and Java so that you can follow the code of your choice of either a very high-level language with advanced features, or a mainstream language.By the end of this book, you’ll be able to build and deploy your own domain-specific languages, capable of compiling and running programs.

Performance Testing with JMeter. Test web applications using Apache JMeter with practical, hands-on examples

Bayo Erinle