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.
Giuseppe Bonaccorso
Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python.This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images.By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges.
Luca Venturi, Krishtof Korda
The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field.You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller.By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers.
Harpreet Singh, Himanshu Sharma
Metasploit has been a crucial security tool for many years. However, there are only a few modules that Metasploit has made available to the public for pentesting web applications. In this book, you'll explore another aspect of the framework – web applications – which is not commonly used. You'll also discover how Metasploit, when used with its inbuilt GUI, simplifies web application penetration testing. The book starts by focusing on the Metasploit setup, along with covering the life cycle of the penetration testing process. Then, you will explore Metasploit terminology and the web GUI, which is available in the Metasploit Community Edition. Next, the book will take you through pentesting popular content management systems such as Drupal, WordPress, and Joomla, which will also include studying the latest CVEs and understanding the root cause of vulnerability in detail. Later, you'll gain insights into the vulnerability assessment and exploitation of technological platforms such as JBoss, Jenkins, and Tomcat. Finally, you'll learn how to fuzz web applications to find logical security vulnerabilities using third-party tools. By the end of this book, you'll have a solid understanding of how to exploit and validate vulnerabilities by working with various tools and techniques.
Anish Chapagain
Web scraping is an essential technique used in many organizations to gather valuable data from web pages. This book will enable you to delve into web scraping techniques and methodologies.The book will introduce you to the fundamental concepts of web scraping techniques and how they can be applied to multiple sets of web pages. You'll use powerful libraries from the Python ecosystem such as Scrapy, lxml, pyquery, and bs4 to carry out web scraping operations. You will then get up to speed with simple to intermediate scraping operations such as identifying information from web pages and using patterns or attributes to retrieve information. This book adopts a practical approach to web scraping concepts and tools, guiding you through a series of use cases and showing you how to use the best tools and techniques to efficiently scrape web pages. You'll even cover the use of other popular web scraping tools, such as Selenium, Regex, and web-based APIs.By the end of this book, you will have learned how to efficiently scrape the web using different techniques with Python and other popular tools.
Hello World! Przygoda z programowaniem dla dzieci i absolutnie początkujących. Wydanie II
Warren Sande, Carter Sande
Nauka programowania to świetny pomysł, ale musimy Cię ostrzec: programowanie wciąga! Jeśli nauczysz się porozumiewać z komputerem w jego języku, szybko zorientujesz się, że napisanie własnej gry, skryptu do złożonych obliczeń czy funkcjonalnej aplikacji do codziennego użytku daje wielką satysfakcję i sprawia mnóstwo radości. Co więcej, programowania można nauczyć się niemal w każdym wieku. Wystarczy odrobina cierpliwości i konsekwencji! Trzymasz w ręce chyba najlepszy podręcznik do nauki programowania dla osób absolutnie początkujących — nawet takich, które komputera używają wyłącznie do przeglądania stron i obsługi poczty. W sposób szczególny nadaje się on dla dzieci, ale skorzystają z niego również dorośli, którzy chcą poznać podstawy programowania. Jasno i klarownie przedstawiono tu wszystkie niezbędne informacje, a liczne (bardzo zabawne) przykłady pozwalają na głębsze zrozumienie prezentowanych treści. Nauka odbywa się w języku Python. Jest to język łatwy w nauce, a przy tym bardzo popularny i wciąż rozwijany. Co więcej, przyswojenie sobie Pythona pozwala na szybką naukę innych języków! W tym podręczniku znajdziesz informacje m.in. o tym: jak przygotować się do pracy: zainstalować Pythona i napisać pierwsze linie kodu czym są i do czego służą zmienne, typy danych, operatory czym jest GUI i jak go napisać jakie są rodzaje pętli, co to są funkcje i na czym polega obsługa zdarzeń jak przygotować symulacje komputerowe Witaj w niezwykłym świecie programowania! Warren Sande — jest inżynierem systemów elektronicznych. Na co dzień korzysta z Pythona zarówno do nauczania programowania, jak i do pisania w pełni profesjonalnych skryptów. Carter Sande — jest uczniem o wielkiej pasji do technologii. Troszczy się o szkolną sieć informatyczną, chętnie pomaga kolegom w rozwiązywaniu problemów z komputerami, a ponadto uwielbia jeździć na rowerze i grać w stare gry wideo.
Pietro Libro, Artem Lajko
This book covers actionable GitOps practices for automated, secure Kubernetes deployments with industry-tested scenarios. You’ll be able to leverage GitOps to tackle cloud-native software delivery challenges, such as preventing data drifts between systems and Git repositories, and ensuring rapid, error-free deployments.The book introduces GitOps core concepts and principles and then delves into integrating version control and GitOps tools such as Argo CD, Flux CD, Helm, and Kustomize with Kubernetes. You’ll learn about scaling GitOps across multiple clusters, architectural designs for efficient cloud-native operations, and the cultural transformation needed to support GitOps adoption within an organization. As you progress, you’ll be able to automate infrastructure and implement CI/CD processes on OpenShift, MS Azure, and AWS platforms using GitOps, Terraform, OpenTofu, and Argo CD. You’ll also explore examples and best practices for integrating observability, enhancing security, managing financial operations (FinOps), and future trends such as AI and sustainability in GitOps.By the end of this book, you’ll have gained the skills you need to apply GitOps strategies for robust Kubernetes and cloud deployments, thereby boosting your productivity and efficiency.
Implementowanie Czystej Architektury w Pythonie
Sebastian Buczyński
Zaawansowane programowanie zaczyna się tam, gdzie kończy się framework Praca programisty wydaje się dziś znacznie prostsza niż kilkanaście lat temu. Wydaje się taka, ponieważ ma on dostęp do niezliczonych bibliotek przypisanych do języków programowania. Gdy pojawia się problem, sięga do biblioteki ― i po sprawie. Problem rozwiązany, zgadza się? I tak, i nie. Owszem, w wypadku prostych projektów wystarczy bazowa znajomość zasad programowania, podstawowa znajomość danego języka i wiedza na temat tego, co zawiera konkretna biblioteka. Tak jednak działa to jedynie przy nieskomplikowanych aplikacjach. Bez wątpienia dziś łatwiej zacząć programować i szybciej można uzyskać mierzalne efekty, ale... ...prawdziwe programowanie zaczyna się poziom wyżej. Na etapie większych projektów. Bo duże systemy, niezależnie od języka, w jakim zostały napisane, zawsze są trudne ― zarówno w rozwijaniu, jak i w utrzymaniu. Książka, którą trzymasz w ręku, została napisana ze świadomością tej programistycznej prawdy. Adresowana do średnio zaawansowanych programistów zajmujących się rozwojem aplikacji internetowych, stanowi kompletny przewodnik po implementacji czystej architektury. Znajdziesz tu także opisy wielu technik, które pomogą Ci zapanować nad projektami rozwijanymi od dłuższego czasu, takich jak strategia testowania czy modularyzacja. Dzięki ich opanowaniu będzie Ci o wiele łatwiej dbać o poprawność funkcjonowania systemów, nad którymi sprawujesz programistyczną pieczę.
Infrastructure as Code with Pulumi. Streamlining Cloud Deployments Using Code
Adora Nwodo
Infrastructure Automation with Pulumi is your ultimate guide to mastering infrastructure as code across multi-cloud environments. This comprehensive resource walks you through setting up Pulumi, deploying across major cloud providers, and confidently scaling complex architectures. Starting with the fundamentals of infrastructure as code, you'll set up Pulumi, learn its core concepts like resources, stacks, and state management, and build your first infrastructure projects. As you progress, you'll explore advanced techniques for deploying on AWS, Azure, Google Cloud, and Kubernetes. You'll also integrate Pulumi into CI/CD pipelines for continuous deployment and automate cloud infrastructure management. You'll dive deep into Pulumi's provider ecosystem, tackle real-world challenges like multi-region, multi-cloud, and hybrid deployments, and ensure compliance using Policy as Code techniques. With practical examples, real-world scenarios, and hands-on exercises, you'll gain the skills to confidently build scalable, secure, and efficient cloud infrastructure using Pulumi. By the end of this book, you'll have mastered Pulumi's advanced capabilities, applied best practices for maintainable and testable infrastructure code, and be ready to migrate existing projects from other IaC tools to Pulumi seamlessly.
Matthew Topol, Wes McKinney
Apache Arrow is an open source, columnar in-memory data format designed for efficient data processing and analytics. This book harnesses the author’s 15 years of experience to show you a standardized way to work with tabular data across various programming languages and environments, enabling high-performance data processing and exchange.This updated second edition gives you an overview of the Arrow format, highlighting its versatility and benefits through real-world use cases. It guides you through enhancing data science workflows, optimizing performance with Apache Parquet and Spark, and ensuring seamless data translation. You’ll explore data interchange and storage formats, and Arrow's relationships with Parquet, Protocol Buffers, FlatBuffers, JSON, and CSV. You’ll also discover Apache Arrow subprojects, including Flight, SQL, Database Connectivity, and nanoarrow. You’ll learn to streamline machine learning workflows, use Arrow Dataset APIs, and integrate with popular analytical data systems such as Snowflake, Dremio, and DuckDB. The latter chapters provide real-world examples and case studies of products powered by Apache Arrow, providing practical insights into its applications.By the end of this book, you’ll have all the building blocks to create efficient and powerful analytical services and utilities with Apache Arrow.
Inteligentna sieć. Algorytmy przyszłości. Wydanie II
Douglas McIlwraith, Haralambos Marmanis, Dmitry Babenko
Określenie „inteligentna sieć” może przywodzić na myśl futurystyczną wizję maszyn przejmujących kontrolę nad światem i niszczących ludzkość, jednak w rzeczywistości jest związane z rozwojem technologii. Związane jest z powstawaniem oprogramowania, które potrafi się uczyć i reagować na zachowania użytkowników. Oznacza też projektowanie i implementację inteligencji maszynowej. Inteligentna sieć rozwija się tu i teraz — znajomość zagadnień uczenia maszynowego i budowy inteligentnych algorytmów staje się bardzo potrzebna inżynierom oprogramowania! Niniejsza książka jest przeznaczona dla osób, które chcą projektować inteligentne algorytmy, a przy tym mają podstawy z zakresu programowania, matematyki i statystyki. Przedstawiono tu schematy projektowe i praktyczne przykłady rozwiązań. Opisano algorytmy, które przetwarzają strumienie danych pochodzące z internetu, a także systemy rekomendacji i klasyfikowania danych za pomocą algorytmów statystycznych, sieci neuronowych i uczenia głębokiego. Mimo że przyswojenie tych zagadnień wymaga wysiłku, bardzo ułatwi implementację nowoczesnych, inteligentnych aplikacji! W tej książce między innymi: wprowadzenie do problemów algorytmów inteligentnych systemy rekomendacji i filtrowanie kolaboratywne wykorzystanie regresji logistycznej do wykrywania oszustw uczenie głębokie, uczenie na żywo i renesans sieci neuronowych podejmowanie decyzji perspektywy inteligentnej sieci Inteligentny algorytm wyławia perły w strumieniach danych! Dr Douglas McIlwraith jest ekspertem w dziedzinie uczenia maszynowego. Zajmuje się analizą danych w londyńskiej agencji reklamowej. Prowadził badania w dziedzinach systemów rozproszonych, robotyki i zabezpieczeń. Dr Haralambos Marmanis jest pionierem w obszarze technik uczenia maszynowego w rozwiązaniach przemysłowych. Od 25 lat rozwija profesjonalne oprogramowanie. Dmitry Babenko projektuje złożone systemy dla firm z takich branż, jak bankowość, ubezpieczenia, zarządzanie łańcuchem dostaw i analityka biznesowa.
Abha Belorkar , Sharath Chandra Guntuku ,...
With so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python.You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements. After you get a hang of the various non-interactive visualization libraries, you'll learn the principles of intuitive and persuasive data visualization, and use Bokeh and Plotly to transform your visuals into strong stories. You'll also gain insight into how interactive data and model visualization can optimize the performance of a regression model.By the end of the course, you'll have a new skill set that'll make you the go-to person for transforming data visualizations into engaging and interesting stories.
Colin Dow
Renowned for its versatility, affordability, and active community support, Raspberry Pi is at the forefront of IoT development. Unlock the vast potential of Raspberry Pi and Raspberry Pi Pico by learning how to develop practical projects with this updated edition of Internet of Things Programming Projects.Written by an expert programmer who’s worked for some of Canada’s largest companies, this book starts with foundational concepts and practical exercises such as building a basic weather indicator, and gradually progressed toward more complex projects. You’ll get to grips with coding nuances and web service integrations that will help you create a sophisticated IoT robot car equipped with motor control, wireless communication, and sensor amalgamation. The book also explores LoRa technology, a game-changer for long-range, low-power communication in your projects, and delves into robot car development by implementing the Robot Operating System (ROS) for advanced control and coordination.Through clear, step-by-step instructions and insightful explanations, you’ll gain the skills and confidence to develop innovative IoT solutions for real-world applications. By the end of the book, you’ll have mastered the intricacies of IoT programming, from harnessing Raspberry Pi's capabilities to seamlessly integrating external components.
Colin Dow
The Internet of Things (IOT) has managed to attract the attention of researchers and tech enthusiasts, since it powerfully combines classical networks with instruments and devices.In Internet of Things Programming Projects, we unleash the power of Raspberry Pi and Python to create engaging projects. In the first part of the book, you’ll be introduced to the Raspberry Pi, learn how to set it up, and then jump right into Python programming. Then, you’ll dive into real-world computing by creating a“Hello World” app using flash LEDs.As you make your way through the chapters, you’ll go back to an age when analog needle meters ruled the world of data display. You’ll learn to retrieve weather data from a web service and display it on an analog needle meter, and build a home security system using the Raspberry Pi. The next project has a modern twist, where we employ the Raspberry Pi to send a signal to a web service that will send you a text when someone is at the door. In the final project, you take what you've learned from the previous two projects and create an IoT robot car that you can use to monitor what your pets are up to when you are away.By the end of this book, you will be well versed in almost every possible way to make your IoT projects stand out.
Serg Masís
Do you want to gain a deeper understanding of your models and better mitigate poor prediction risks associated with machine learning interpretation? If so, then Interpretable Machine Learning with Python deserves a place on your bookshelf.We’ll be starting off with the fundamentals of interpretability, its relevance in business, and exploring its key aspects and challenges. As you progress through the chapters, you'll then focus on how white-box models work, compare them to black-box and glass-box models, and examine their trade-off. You’ll also get you up to speed with a vast array of interpretation methods, also known as Explainable AI (XAI) methods, and how to apply them to different use cases, be it for classification or regression, for tabular, time-series, image or text. In addition to the step-by-step code, this book will also help you interpret model outcomes using examples. You’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability. The methods you’ll explore here range from state-of-the-art feature selection and dataset debiasing methods to monotonic constraints and adversarial retraining.By the end of this book, you'll be able to understand ML models better and enhance them through interpretability tuning.
Introduction to Algorithms. A Comprehensive Guide for Beginners: Unlocking Computational Thinking
Cuantum Technologies LLC
Begin your journey into the fascinating world of algorithms with this comprehensive course. Starting with an introduction to the basics, you will learn about pseudocode and flowcharts, the fundamental tools for representing algorithms. As you progress, you'll delve into the efficiency of algorithms, understanding how to evaluate and optimize them for better performance. The course will also cover various basic algorithm types, providing a solid foundation for further exploration.You will explore specific categories of algorithms, including search and sort algorithms, which are crucial for managing and retrieving data efficiently. You will also learn about graph algorithms, which are essential for solving problems related to networks and relationships. Additionally, the course will introduce you to the data structures commonly used in algorithms.Towards the end, the focus shifts to algorithm design techniques and their real-world applications. You will discover various strategies for creating efficient and effective algorithms and see how these techniques are applied in real-world scenarios. By the end of the course, you will have a thorough understanding of algorithmic principles and be equipped with the skills to apply them in your technical career.
Luiz Felipe Martins
If you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.