Python
W kategorii Python zostały zebrane podręczniki poruszające tematykę programowania z zastosowaniem praktycznie niezależnego sprzętowo, dostępnego na licencji Open Source języka. Książki przedstawią Wam wszechstronności i elastyczności Pythona a także różne typy tworzenia kodu poprzez programowanie strukturalne, obiektowe czy funkcjonalne.
Nauczycie się tworzyć aplikacje sieciowe o dowolnym przeznaczeniu, komunikujące się z systemami operacyjnymi, lub korzystające z baz danych. Techniki analizy składni, przetwarzanie tekstu czy rozłożenie obciążenia programu na wiele wątków i procesów przestanie być problematyczne.
Saif Ahmed, Quan Hua, Shams Ul Azeem
Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you’ll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data ?ow graphs, training, and the visualization of performance with TensorBoard—all within an example-rich context using problems from multiple industries. You’ll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you’ll implement a complete real-life production system from training to serving a deep learning model. As you advance you’ll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you’ll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim.By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment.
Rich Collier, Camilla Montonen, Bahaaldine Azarmi
Elastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively. With the addition of machine learning, a key commercial feature, the Elastic Stack makes this process even more efficient. This updated second edition of Machine Learning with the Elastic Stack provides a comprehensive overview of Elastic Stack's machine learning features for both time series data analysis as well as for classification, regression, and outlier detection.The book starts by explaining machine learning concepts in an intuitive way. You'll then perform time series analysis on different types of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you'll deploy machine learning within Elastic Stack for logging, security, and metrics. Finally, you'll discover how data frame analysis opens up a whole new set of use cases that machine learning can help you with.By the end of this Elastic Stack book, you'll have hands-on machine learning and Elastic Stack experience, along with the knowledge you need to incorporate machine learning in your distributed search and data analysis platform.
Mapping with ArcGIS Pro. Design accurate and user-friendly maps to share the story of your data
Amy Rock, Ryan Malhoski
ArcGIS Pro is a geographic information system for working with maps and geographic information. This book will help you create visually stunning maps that increase thelegibility of the stories being mapped and introduce visual and design concepts intoa traditionally scientific, data-driven process. The book begins by outlining the stepsof gathering data from authoritative sources and lays out the workflow of creating a great map. Once the plan is in place you will learn how to organize the Contents Pane in ArcGIS Pro and identify the steps involved in streamlining the production process. Then you will learn Cartographic Design techniques using ArcGIS Pro's feature set to organize thepage structure and create a custom set of color swatches. You will be then exposedto the techniques required to ensure your data is clear and legible no matter the sizeor scale of your map. The later chapters will help you understand the various projectionsystems, trade-offs between them, and the proper applications of them to make sureyour maps are accurate and visually appealing. Finally, you will be introducedto the ArcGIS Online ecosystem and how ArcGIS Pro can utilize it within theapplication. You will learn Smart Mapping, a new feature of ArcGIS Online that willhelp you to make maps that are visually stunning and useful.By the end of this book, you will feel more confident in making appropriate cartographic decisions.
James Freeman, Jesse Keating
Ansible is a modern, YAML-based automation tool (built on top of Python, one of the world’s most popular programming languages) with a massive and ever-growing user base. Its popularity and Python underpinnings make it essential learning for all in the DevOps space.This fourth edition of Mastering Ansible provides complete coverage of Ansible automation, from the design and architecture of the tool and basic automation with playbooks to writing and debugging your own Python-based extensions.You'll learn how to build automation workflows with Ansible’s extensive built-in library of collections, modules, and plugins. You'll then look at extending the modules and plugins with Python-based code and even build your own collections — ultimately learning how to give back to the Ansible community.By the end of this Ansible book, you'll be confident in all aspects of Ansible automation, from the fundamentals of playbook design to getting under the hood and extending and adapting Ansible to solve new automation challenges.
James Freeman, Jesse Keating
Automation is essential for success in the modern world of DevOps. Ansible provides a simple, yet powerful, automation engine for tackling complex automation challenges.This book will take you on a journey that will help you exploit the latest version's advanced features to help you increase efficiency and accomplish complex orchestrations. This book will help you understand how Ansible 2.7 works at a fundamental level and will also teach you to leverage its advanced capabilities. Throughout this book, you will learn how to encrypt Ansible content at rest and decrypt data at runtime. Next, this book will act as an ideal resource to help you master the advanced features and capabilities required to tackle complex automation challenges. Later, it will walk you through workflows, use cases, orchestrations, troubleshooting, and Ansible extensions. Lastly, you will examine and debug Ansible operations, helping you to understand and resolve issues.By the end of the book, you will be able to unlock the true power of the Ansible automation engine and tackle complex, real- world actions with ease.
Krishnendu Kar
Computer vision allows machines to gain human-level understanding to visualize, process, and analyze images and videos. This book focuses on using TensorFlow to help you learn advanced computer vision tasks such as image acquisition, processing, and analysis. You'll start with the key principles of computer vision and deep learning to build a solid foundation, before covering neural network architectures and understanding how they work rather than using them as a black box. Next, you'll explore architectures such as VGG, ResNet, Inception, R-CNN, SSD, YOLO, and MobileNet. As you advance, you'll learn to use visual search methods using transfer learning. You'll also cover advanced computer vision concepts such as semantic segmentation, image inpainting with GAN's, object tracking, video segmentation, and action recognition. Later, the book focuses on how machine learning and deep learning concepts can be used to perform tasks such as edge detection and face recognition. You'll then discover how to develop powerful neural network models on your PC and on various cloud platforms. Finally, you'll learn to perform model optimization methods to deploy models on edge devices for real-time inference. By the end of this book, you'll have a solid understanding of computer vision and be able to confidently develop models to automate tasks.
Quan Nguyen
Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming.Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples.By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language
Uroš Kastelic, József Zoltán Vadkerti
Mastering DevOps on Microsoft Power Platform is your guide to revolutionizing business-critical solution development. Written by two Microsoft Technology Specialists with extensive experience in enterprise-scale Power Platform implementations and DevOps practices, this book teaches you how to design, build, and secure efficient DevOps processes by adapting custom software development practices to the Power Platform toolset, dramatically reducing time, cost, and errors in app modernization and quality assurance.The book introduces application life cycle management (ALM) and DevOps-enabled architecture, design patterns, and CI/CD practices, showing you why companies adopt DevOps with Power Platform. You'll master environment and solution management using Dataverse, Git, the Power Platform CLI, Azure DevOps, and GitHub Copilot.Implementing the shift-left approach in DevSecOps using GitHub Advanced Security features, you’ll create a Power Platform tenant governed by controls, automated tests, and backlog management. You’ll also discover advanced concepts, such as fusion architecture, pro-dev extensibility, and AI-infused applications, along with tips to avoid common pitfalls.By the end of this book, you’ll be able to build CI/CD pipelines from development to production, enhancing the life cycle of your business solutions on Power Platform.
Sherwin John C. Tragura
Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web and API Development will take you on an exhaustive tour of the Flask environment and teach you how to build a production-ready application.You’ll start by installing Flask and grasping fundamental concepts, such as MVC and ORM database access. Next, you’ll master structuring applications for scalability through Flask blueprints. As you progress, you’ll explore both SQL and NoSQL databases while creating REST APIs and implementing JWT authentication, and improve your skills in role-based access security, utilizing LDAP, OAuth, OpenID, and databases. The new project structure, managed by context managers, as well as ASGI support, has revolutionized Flask, and you’ll get to grips with these crucial upgrades. You'll also explore out-of-the-box integrations with technologies, such as RabbitMQ, Celery, NoSQL databases, PostgreSQL, and various external modules. The concluding chapters discuss enterprise-related challenges where Flask proves its mettle as a core solution.By the end of this book, you’ll be well-versed with Flask, seeing it not only as a lightweight web and API framework, but also as a potent problem-solving tool in your daily work, addressing integration and enterprise issues alongside Django and FastAPI.
Daniel Gaspar, Jack Stouffer
Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web Development will take you on a complete tour of the Flask environment and teach you how to build a production-ready application. You'll begin by learning about the installation of Flask and basic concepts such as MVC and accessing a database using an ORM. You will learn how to structure your application so that it can scale to any size with the help of Flask Blueprints. You'll then learn how to use Jinja2 templates with a high level of expertise. You will also learn how to develop with SQL or NoSQL databases, and how to develop REST APIs and JWT authentication. Next, you'll move on to build role-based access security and authentication using LDAP, OAuth, OpenID, and database. Also learn how to create asynchronous tasks that can scale to any load using Celery and RabbitMQ or Redis. You will also be introduced to a wide range of Flask extensions to leverage technologies such as cache, localization, and debugging. You will learn how to build your own Flask extensions, how to write tests, and how to get test coverage reports. Finally, you will learn how to deploy your application on Heroku and AWS using various technologies, such as Docker, CloudFormation, and Elastic Beanstalk, and will also learn how to develop Jenkins pipelines to build, test, and deploy applications.
Silas Toms, Paul Crickard, Eric van Rees
Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis.You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Shammunul Islam, Simon Miles, Kurt Menke, GISP,...
QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to proprietary GIS software. Although QGIS is described as intuitive, it is also, by default, complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work.
Mohsin Hijazee, Mohsin Shafique
Mastering GUI Programming with Python. Develop impressive cross-platform GUI applications with PyQt
Alan D. Moore
PyQt5 has long been the most powerful and comprehensive GUI framework available for Python, yet there is a lack of cohesive resources available for Python programmers to learn how to use it. This book will be your comprehensive guide to exploring GUI development with PyQt5.You will get started with an introduction to PyQt5, before going on to develop stunning GUIs with modern features. You will learn how to build forms using QWidgets and delve into important aspects of GUI development such as layouts, size policies, and event-driven programming. Moving ahead, you’ll discover PyQt5’s most powerful features through chapters on audio-visual programming with QtMultimedia, database-driven software with QtSQL, and web browsing with QtWebEngine. Next, in-depth coverage of multithreading and asynchronous programming will help you run tasks asynchronously and build high-concurrency processes with ease. In later chapters, you’ll gain insights into QOpenGLWidget, along with mastering techniques for creating 2D graphics with QPainter. You’ll also explore PyQt on a Raspberry Pi and interface it with remote systems using QtNetwork. Finally, you will learn how to distribute your applications using setuptools and PyInstaller.By the end of this book, you will have the skills you need to develop robust GUI applications using PyQt.
Giuseppe Bonaccorso
Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains.You will use all the modern libraries from the Python ecosystem – including NumPy and Keras – to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensemble learning, and how to use TensorFlow 2.x to train effective deep neural networks.By the end of this book, you will be ready to implement and solve end-to-end machine learning problems and use case scenarios.
Gavin Hackeling
Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model.This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance.By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.
Alexey Kleymenov, Amr Thabet
With the ever-growing proliferation of technology, the risk of encountering malicious code or malware has also increased. Malware analysis has become one of the most trending topics in businesses in recent years due to multiple prominent ransomware attacks. Mastering Malware Analysis explains the universal patterns behind different malicious software types and how to analyze them using a variety of approaches. You will learn how to examine malware code and determine the damage it can possibly cause to your systems to ensure that it won't propagate any further. Moving forward, you will cover all aspects of malware analysis for the Windows platform in detail. Next, you will get to grips with obfuscation and anti-disassembly, anti-debugging, as well as anti-virtual machine techniques. This book will help you deal with modern cross-platform malware. Throughout the course of this book, you will explore real-world examples of static and dynamic malware analysis, unpacking and decrypting, and rootkit detection. Finally, this book will help you strengthen your defenses and prevent malware breaches for IoT devices and mobile platforms. By the end of this book, you will have learned to effectively analyze, investigate, and build innovative solutions to handle any malware incidents.
Mastering Matplotlib 2.x. Effective Data Visualization techniques with Python
Benjamin Walter Keller
In this book, you’ll get hands-on with customizing your data plots with the help of Matplotlib. You’ll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You’ll explore non-trivial layouts, Pylab customization, and more about tile configuration. You’ll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you’ll explore them further in this book. You’ll delve into niche plots and visualize ordinal and tabular data. In this book, you’ll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you’ll learn how to create interactive plots with the help of Jupyter.Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook
Umit Mert Cakmak, Mert Cuhadaroglu
NumPy is one of the most important scientific computing libraries available for Python. Mastering Numerical Computing with NumPy teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts.Beginning with NumPy's arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling. You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system.By the end of this book, you will have become an expert in handling and performing complex data manipulations.
Steven F. Lott
Object-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language's unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you'll be shown how to effectively implement OOP in Python, and even explore Python 3.x. Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design offers the best performance. Next, you'll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you'll discover how essential it is to locate the best algorithms and optimal data structures for developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs.By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python.
Alberto Fernández Villán
OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language.In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras.By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands.
Ashish Kumar
pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains.An update to our highly successful previous edition with new features, examples, updated code, and more, this book is an in-depth guide to get the most out of pandas for data analysis. Designed for both intermediate users as well as seasoned practitioners, you will learn advanced data manipulation techniques, such as multi-indexing, modifying data structures, and sampling your data, which allow for powerful analysis and help you gain accurate insights from it. With the help of this book, you will apply pandas to different domains, such as Bayesian statistics, predictive analytics, and time series analysis using an example-based approach. And not just that; you will also learn how to prepare powerful, interactive business reports in pandas using the Jupyter notebook.By the end of this book, you will learn how to perform efficient data analysis using pandas on complex data, and become an expert data analyst or data scientist in the process.
