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Python for ArcGIS Pro
Python for ArcGIS Pro

Integrating Python into your day-to-day ArcGIS work is highly recommended when dealing with large amounts of geospatial data. Python for ArcGIS Pro aims to help you get your work done faster, with greater repeatability and higher confidence in your results. Starting from programming basics and building in complexity, two experienced ArcGIS professionals-turned-Python programmers teach you how to incorporate scripting at each step: automating the production of maps for print, managing data between ArcGIS Pro and ArcGIS Online, creating custom script tools for sharing, and then running data analysis and visualization on top of the ArcGIS geospatial library, all using Python. You'll use ArcGIS Pro Notebooks to explore and analyze geospatial data, and write data engineering scripts to manage ongoing data processing and data transfers. This exercise-based book also includes three rich real-world case studies, giving you an opportunity to apply and extend the concepts you studied earli ...
Simplifying Android Development with Coroutines and Flows
Simplifying Android Development with Coroutines and Flows

Coroutines and flows are the new recommended way for developers to carry out asynchronous programming in Android using simple, modern, and testable code. This book will teach you how coroutines and flows work and how to use them in building Android applications, along with helping you to develop modern Android applications with asynchronous programming using real data. The book begins by showing you how to create and handle Kotlin coroutines on Android. You'll explore asynchronous programming in Kotlin, and understand how to test Kotlin coroutines. Next, you'll learn about Kotlin flows on Android, and have a closer look at using Kotlin flows by getting to grips with handling flow cancellations and exceptions and testing the flows. By the end of this book, you'll have the skills you need to build high-quality and maintainable Android applications using coroutines and flows. ...
SAP HANA Cloud in a Nutshell
SAP HANA Cloud in a Nutshell

This book introduces SAP HANA Cloud and helps you develop an understanding of its key features, including technology, architecture, and data modeling. SAP HANA Cloud in a Nutshell will help you develop the skills needed to use the core features of the completely managed and in-memory cloud-based data foundation available in the SAP Business Technology Platform. The book covers modern modeling concepts and equips you with practical knowledge to unleash the best use of SAP HANA Cloud. As you progress, you will learn how to provision your own SAP HANA Cloud instance, understand how to work with different roles, and work with data modeling for analytical and transactional use cases. Additionally, you will learn how to pilot SAP BTP Cockpit and work with entitlements, quotas, account structure, spaces, instances, and cloud providers. You will learn how to perform administration tasks such as stop and start an SAP HANA Cloud instance and make it available for use. To fully leverage th ...
Exploring Graphs with Elixir
Exploring Graphs with Elixir

Data is everywhere - it's just not very well connected, which makes it super hard to relate dataset to dataset. Using graphs as the underlying glue, you can readily join data together and create navigation paths across diverse sets of data. Add Elixir, with its awesome power of concurrency, and you'll soon be mastering data networks. Learn how different graph models can be accessed and used from within Elixir and how you can build a robust semantics overlay on top of graph data structures. We'll start from the basics and examine the main graph paradigms. Get ready to embrace the world of connected data! Graphs provide an intuitive and highly flexible means for organizing and querying huge amounts of loosely coupled data items. These data networks, or graphs in math speak, are typically stored and queried using graph databases. Elixir, with its noted support for fault tolerance and concurrency, stands out as a language eminently suited to processing sparsely connected and distribute ...
Python for Data Science
Python for Data Science

Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds. Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities. You'll learn how to write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques for use cases in business management, marketing, and decision support. You will discover Python's rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science, including NumPy, pandas, scikit-learn, matplotlib, and more. Examples show how to load data in various formats, how to streamline, group, and aggregate data sets, and how to create charts, maps, and other visualizations. Later chapters go in-depth with demonstrations of real-world data applications, including using location data to power a taxi service, market basket ...
3D Deep Learning with Python
3D Deep Learning with Python

With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
Jira 8 Essentials, 6th Edition
Jira 8 Essentials, 6th Edition

This new and improved sixth edition comes with the latest Jira 8.21 Data Center offerings, with enhanced features such as clustering, advanced roadmaps, custom field optimization, and tools to track and manage tasks for your projects. This comprehensive guide to Jira 8.20.x LTS version provides updated content on project tracking, issue and field management, workflows, Jira Service Management, and security. The book begins by showing you how to plan and set up a new Jira instance from scratch before getting you acquainted with key features such as emails, workflows, and business processes. You'll also get to grips with Jira's data hierarchy and design and work with projects. Since Jira is used for issue management, this book will help you understand the different issues that can arise in your projects. As you advance, you'll create new screens from scratch and customize them to suit your requirements. Workflows, business processes, and guides on setting up incoming and outgoing mail ...
Kafka: The Definitive Guide, 2nd Edition
Kafka: The Definitive Guide, 2nd Edition

Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes. Engineers from Confluent and LinkedIn responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. ...
Python for Geospatial Data Analysis
Python for Geospatial Data Analysis

In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. ...
Learning Tableau 2022, 5th Edition
Learning Tableau 2022, 5th Edition

Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau's latest features, such as dashboard extensions, Explain Data, and integration with CRM Analytics (Einstein Analytics), which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You'll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources wit ...
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