ArcGIS Pro 2.x Cookbook. Create, manage, and share geographic maps, data, and analytical models using ArcGIS Pro

Tripp Corbin

ArcGIS is Esri's catalog of GIS applications with powerful tools for visualizing, maintaining, and analyzing data. ArcGIS makes use of the modern ribbon interface and 64-bit processing to increase the speed and efficiency of using GIS. It allows users to create amazing maps in both 2D and 3D quickly and easily. If you want to gain a thorough understanding of the various data formats that can be used in ArcGIS Pro and shared via ArcGIS Online, then this book is for you. Beginning with a refresher on ArcGIS Pro and how to work with projects, this book will quickly take you through recipes about using various data formats supported by the tool. You will learn the limits of each format, such as Shapefiles, Geodatabase, and CAD files, and learn how to link tables from outside sources to existing GIS data to expand the amount of data that can be used in ArcGIS. You'll learn methods for editing 2D and 3D data using ArcGIS Pro and how topology can be used to ensure data integrity. Lastly the book will show you how data and maps can be shared via ArcGIS Online and used with web and mobile applications.

Architektura aplikacji w Pythonie. TDD, DDD i rozwój mikrousług reaktywnych

Harry Percival, Bob Gregory

Architektura aplikacji w Pythonie. TDD, DDD i rozwój mikrousług reaktywnych Python zyskuje coraz większą popularność i jest wykorzystywany do tworzenia bardzo różnych aplikacji, jednak projektowanie dużych, niezawodnych systemów w tym języku bywa wyzwaniem. Rozwijanie złożonych systemów o wysokiej jakości wymaga zastosowania odpowiedniej architektury. Trudno w Pythonie stosować takie wysokopoziomowe wzorce projektowe jak architektura sześciokątna, architektura oparta na zdarzeniach czy wzorce zalecane dla projektowania dziedzinowego (DDD). Sytuacji nie poprawia również to, że klasyczna literatura dotycząca metod zarządzania złożonością aplikacji zawiera przykłady kodu napisanego w Javie lub C#. Programiści Pythona często więc uznają takie książki za mało przydatne w swojej pracy. Ten praktyczny przewodnik przybliży projektantom pracującym w Pythonie sprawdzone wzorce architektury, które ułatwiają zapanowanie nad złożonością aplikacji i pozwalają najlepiej wykorzystać zestawy testów. Prezentację poszczególnych wzorców architektury oparto na przykładowej, stopniowo rozbudowywanej aplikacji. Podejście to pozwoliło na pokazanie zalet metodyki TDD. Z kolei w rozdziałach poświęconych modelowaniu dziedzinowemu zwrócono uwagę na unikanie jakichkolwiek zależności zewnętrznych przy równoczesnym zapewnieniu integralności danych. Wśród ciekawszych koncepcji warto wskazać wykorzystywanie zdarzeń w roli wzorca integracji usług w architekturze mikrousługowej. Niejako przy okazji zaprezentowano praktyczne strony stosowania kilku frameworków i technologii Pythona, między innymi Flask, SQLAlchemy, pytest, Docker i Redis. W tej książce między innymi: modelowanie dziedzinowe i stosowanie wzorców DDD jednostki, obiekty wartości i agregaty w architekturze domenowej tworzenie modeli bez zbędnych zależności zdarzenia, polecenia i szyna wiadomości wzorce architektury zdarzeniowej i mikrousług reaktywnych Architektura nowoczesnych aplikacji w Pythonie: rozwiązania dla poważnych systemów!

ArcPy and ArcGIS - Geospatial Analysis with Python. Use the ArcPy module to automate the analysis and mapping of geospatial data in ArcGIS

Silas Toms, Silas Toms

ArcPy and ArcGIS. Automating ArcGIS for Desktop and ArcGIS Online with Python - Second Edition

Silas Toms, Dara OBeirne

ArcGIS allows for complex analyses of geographic information. The ArcPy module is used to script these ArcGIS analyses, providing a productive way to perform geo-analyses and automate map production.The second edition of the book focuses on new Python tools, such as the ArcGIS API for Python. Using Python, this book will guide you from basic Python scripting to advanced ArcPy script tools.This book starts off with setting up your Python environment for ArcGIS automation. Then you will learn how to output maps using ArcPy in MXD and update feature class in a geodatabase using arcpy and ArcGIS Online. Next, you will be introduced to ArcREST library followed by examples on querying, updating and manipulating ArcGIS Online feature services. Further, you will be enabling your scripts in the browser and directly interacting with ArcGIS Online using Jupyter notebook. Finally, you can learn ways to use of ArcPy to control ArcGIS Enterprise and explore topics on deployments, data quality assurances, data updates, version control, and editing safeguards.By the end of the book, you will be equipped with the knowledge required to create automated analysis with administration reducing the time-consuming nature of GIS.

Artificial Intelligence and Machine Learning Fundamentals. Develop real-world applications powered by the latest AI advances

Zsolt Nagy

Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law.By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!

Artificial Intelligence By Example. Acquire advanced AI, machine learning, and deep learning design skills - Second Edition

Denis Rothman

AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples.This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs).This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing.By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.

Artificial Intelligence for IoT Cookbook. Over 70 recipes for building AI solutions for smart homes, industrial IoT, and smart cities

Michael Roshak

Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users’ lives easier. With this AI cookbook, you’ll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications.Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You’ll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you’ll learn how to deploy models and improve their performance with ease.By the end of this book, you’ll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems.

Artificial Intelligence with Python. A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

Prateek Joshi

Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more.Starting with AI basics you'll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.