Python

Applied Unsupervised Learning with Python. Discover hidden patterns and relationships in unstructured data with Python

Benjamin Johnston, Aaron Jones , Christopher Kruger

Unsupervised learning is a useful and practical solution in situations where labeled data is not available.Applied Unsupervised Learning with Python guides you in learning the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The book begins by explaining how basic clustering works to find similar data points in a set. Once you are well-versed with the k-means algorithm and how it operates, you’ll learn what dimensionality reduction is and where to apply it. As you progress, you’ll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. Finally, you will be able to put your knowledge to work through interesting activities such as performing a Market Basket Analysis and identifying relationships between different products.By the end of this book, you will have the skills you need to confidently build your own models using Python.

Applying Math with Python. Practical recipes for solving computational math problems using Python programming and its libraries

Sam Morley

Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain.The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python’s scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.

ArcGIS By Example. Develop three engaging ArcGIS applications to address your real-world mapping scenarios

Hussein Nasser

ArcGIS is a geographic information system (GIS) for working with maps and geographic information. It is considered the turnkey solution to creating and sharing interactive maps. ArcGIS is designed to work the way you work. With nothing to install and set up, ArcGIS helps you make your work productive from day one.The book covers the design and development of three ArcGIS applications to guide the readers in crafting their own GIS solution as per their requirements. The book begins by giving you a refresher on the concepts of ArcGIS. Without wasting any time, you’ll begin with developing your first ArcGIS application. You will be developing a cell tower analysis tool. Following this, you will be guided through mapping signal strength and real - time manoeuvring in your GIS system. You will then move on to the second application of the book: a restaurant mapping system. The application will allow tourists to browse restaurants on a map, according to their preferences. Next, you will learn how to work with reviews and ratings and also cover some of the advanced searching options offered by ArcGIS. You will then make use of advanced ArcObjects to develop your third application: an excavation planning manager. The book will conclude by teaching you how work out excavation cost calculations and also saving and retrieving your excavation designs.

ArcGIS for Desktop Cookbook. Over 60 hands-on recipes to help you become a more productive ArcGIS for Desktop user

Daniela C Docan

This book is a good companion to get you quickly acquainted with everything you need to increase your productivity with the ArcGIS Desktop.It would be helpful to have a bit of familiarity with basic GIS concepts.If you have no previous experience with ArcGIS, this book will still be helpful for you because it will help you catch up to the acquainted users from a practical point of view.

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

Tripp Corbin, GISP

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

Silas Toms, Jerry Davis, 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.

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

Silas Toms

If you are a GIS student or professional who needs an understanding of how to use ArcPy to reduce repetitive tasks and perform analysis faster, this book is for you. It is also a valuable book for Python programmers who want to understand how to automate geospatial analyses.