Python

Designing Professional Websites with Odoo Website Builder. Create and customize state-of-the-art websites and e-commerce apps for your modern business needs

Sainu Nannat

The Odoo website builder is an operational tool in the Odoo platform that allows you to design, develop, and manage a website. This book introduces and explains all the features of the Odoo website builder that will help you to be more productive while creating websites.The book starts with an overview of the Odoo website builder, its functionalities, and the tools it offers. Using descriptive illustrations and practical examples, you’ll gain detailed insights into the block operations of the Odoo website builder and learn how to work with structure blocks, features blocks, and dynamic content blocks. As you advance, you’ll discover how to use the HTML, CSS, or JS editor in Odoo website builder applications for customization. This Odoo book will take you through the different aspects of website building and show you how e-commerce websites can be designed and developed using website builder applications. You’ll build a website, manage it, and run a discussion forum in Odoo using the website builder, and apply your knowledge to add a live chat tool that can be incorporated into your website using the Odoo website builder.By the end of this book, you’ll have gained a solid understanding of the Odoo website builder and be able to leverage its features to develop your own website.

Developing Kaggle Notebooks. Pave your way to becoming a Kaggle Notebooks Grandmaster

Gabriel Preda, D. Sculley, Anthony Goldbloom

Developing Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques.For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable.Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.

Digital Forensics and Incident Response. Incident response techniques and procedures to respond to modern cyber threats - Second Edition

Gerard Johansen

An understanding of how digital forensics integrates with the overall response to cybersecurity incidents is key to securing your organization's infrastructure from attacks. This updated second edition will help you perform cutting-edge digital forensic activities and incident response.After focusing on the fundamentals of incident response that are critical to any information security team, you’ll move on to exploring the incident response framework. From understanding its importance to creating a swift and effective response to security incidents, the book will guide you with the help of useful examples. You’ll later get up to speed with digital forensic techniques, from acquiring evidence and examining volatile memory through to hard drive examination and network-based evidence. As you progress, you’ll discover the role that threat intelligence plays in the incident response process. You’ll also learn how to prepare an incident response report that documents the findings of your analysis. Finally, in addition to various incident response activities, the book will address malware analysis, and demonstrate how you can proactively use your digital forensic skills in threat hunting.By the end of this book, you’ll have learned how to efficiently investigate and report unwanted security breaches and incidents in your organization.

Distributed Data Systems with Azure Databricks. Create, deploy, and manage enterprise data pipelines

Alan Bernardo Palacio

Microsoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models. Databricks' advanced features enable developers to process, transform, and explore data. Distributed Data Systems with Azure Databricks will help you to put your knowledge of Databricks to work to create big data pipelines. The book provides a hands-on approach to implementing Azure Databricks and its associated methodologies that will make you productive in no time. Complete with detailed explanations of essential concepts, practical examples, and self-assessment questions, you’ll begin with a quick introduction to Databricks core functionalities, before performing distributed model training and inference using TensorFlow and Spark MLlib. As you advance, you’ll explore MLflow Model Serving on Azure Databricks and implement distributed training pipelines using HorovodRunner in Databricks. Finally, you’ll discover how to transform, use, and obtain insights from massive amounts of data to train predictive models and create entire fully working data pipelines. By the end of this MS Azure book, you’ll have gained a solid understanding of how to work with Databricks to create and manage an entire big data pipeline.

Distributed Machine Learning with Python. Accelerating model training and serving with distributed systems

Guanhua Wang

Reducing time cost in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time. You'll begin by exploring how distributed systems work in the machine learning area and how distributed machine learning is applied to state-of-the-art deep learning models. As you advance, you'll see how to use distributed systems to enhance machine learning model training and serving speed. You'll also get to grips with applying data parallel and model parallel approaches before optimizing the in-parallel model training and serving pipeline in local clusters or cloud environments. By the end of this book, you'll have gained the knowledge and skills needed to build and deploy an efficient data processing pipeline for machine learning model training and inference in a distributed manner.

Distributed .NET with Microsoft Orleans. Build robust and highly scalable distributed applications without worrying about complex programming patterns

Bhupesh Guptha Muthiyalu, Suneel Kumar Kunani

Building distributed applications in this modern era can be a tedious task as customers expect high availability, high performance, and improved resilience. With the help of this book, you'll discover how you can harness the power of Microsoft Orleans to build impressive distributed applications.Distributed .NET with Microsoft Orleans will demonstrate how to leverage Orleans to build highly scalable distributed applications step by step in the least possible time and with minimum effort. You'll explore some of the key concepts of Microsoft Orleans, including the Orleans programming model, runtime, virtual actors, hosting, and deployment. As you advance, you'll become well-versed with important Orleans assets such as grains, silos, timers, and persistence. Throughout the book, you'll create a distributed application by adding key components to the application as you progress through each chapter and explore them in detail.By the end of this book, you'll have developed the confidence and skills required to build distributed applications using Microsoft Orleans and deploy them in Microsoft Azure.

Django 1.0 Template Development. A practical guide to Django template development with custom tags, filters, multiple templates, caching, and more

Scott Newman

This book is designed for readers who learn by doing and employs many examples and screenshots to let the reader dig in and start coding. This book isn't designed to be a reference; instead it has a practical, example-driven approach that teaches you by following along with the examples in the chapters. When you have completed this book, you will fully understand how the template system works, how to extend it when you have specialized needs, and how to optimize the performance and usability of your content. This book is for web developers and template authors who want to fully understand and utilize the Django template system. The reader should have completed the introductory tutorials on the Django project's website and some experience with the framework will be very helpful. Basic knowledge of Python and HTML is assumed.

Django 2 by Example. Build powerful and reliable Python web applications from scratch

Antonio Melé

If you want to learn the entire process of developing professional web applications with Django 2, then this book is for you. You will walk through the creation of four professional Django 2 projects, teaching you how to solve common problems and implement best practices.You will learn how to build a blog application, a social image bookmarking website, an online shop and an e-learning platform. The book will teach you how to enhance your applications with AJAX, create RESTful APIs and set up a production environment for your Django 2 projects. The book walks you through the creation of real-world applications, solving common problems, and implementing best practices. By the end of this book, you will have a deep understanding of Django 2 and how to build advanced web applications.