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Psychologia
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Audiobooki
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Biznes i ekonomia
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Dla dzieci
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Edukacja
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Nauki przyrodnicze
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Nauki społeczne
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Popularnonaukowe i akademickie
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Poradniki
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Poradniki zawodowe i specjalistyczne
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Prawo
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Przewodniki i podróże
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Psychologia
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Religia
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Sport, fitness, diety
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Technika i mechanika
Kursy video
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Bazy danych
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Big Data
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Biznes, ekonomia i marketing
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Cyberbezpieczeństwo
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Data Science
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DevOps
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Dla dzieci
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Elektronika
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Grafika/Wideo/CAX
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Gry
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Microsoft Office
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Narzędzia programistyczne
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Programowanie
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Rozwój osobisty
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Sieci komputerowe
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Systemy operacyjne
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Testowanie oprogramowania
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Urządzenia mobilne
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UX/UI
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Web development
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Zarządzanie
Podcasty
Kamal Arora, Erik Farr, John Gilbert, Piyum Zonooz
Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems.This Learning Path teaches you everything you need to know for designing industry-grade cloud applications and efficiently migrating your business to the cloud. It begins by exploring the basic patterns that turn your database inside out to achieve massive scalability. You’ll learn how to develop cloud native architectures using microservices and serverless computing as your design principles. Then, you’ll explore ways to continuously deliver production code by implementing continuous observability in production. In the concluding chapters, you’ll learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform, and understand the future trends and expectations of cloud providers.By the end of this Learning Path, you’ll have learned the techniques to adopt cloud native architectures that meet your business requirements. This Learning Path includes content from the following Packt products:• Cloud Native Development Patterns and Best Practices by John Gilbert• Cloud Native Architectures by Erik Farr et al.
Adversarial Tradecraft in Cybersecurity. Offense versus defense in real-time computer conflict
Little has been written about what to do when live hackers are on your system and running amok. Even experienced hackers tend to choke up when they realize the network defender has caught them and is zoning in on their implants in real time. This book will provide tips and tricks all along the kill chain of an attack, showing where hackers can have the upper hand in a live conflict and how defenders can outsmart them in this adversarial game of computer cat and mouse.This book contains two subsections in each chapter, specifically focusing on the offensive and defensive teams. It begins by introducing you to adversarial operations and principles of computer conflict where you will explore the core principles of deception, humanity, economy, and more about human-on-human conflicts. Additionally, you will understand everything from planning to setting up infrastructure and tooling that both sides should have in place.Throughout this book, you will learn how to gain an advantage over opponents by disappearing from what they can detect. You will further understand how to blend in, uncover other actors’ motivations and means, and learn to tamper with them to hinder their ability to detect your presence. Finally, you will learn how to gain an advantage through advanced research and thoughtfully concluding an operation.By the end of this book, you will have achieved a solid understanding of cyberattacks from both an attacker’s and a defender’s perspective.
Value Stream Management (VSM) opens the door to maximizing your DevOps pipeline investments by improving flows and eliminating waste. VSM and DevOps together deliver value stream improvements across enterprises for a competitive advantage in the digital world. Driving DevOps with Value Stream Management provides a comprehensive review and analysis of industry-proven VSM methods and tools to integrate, streamline, and orchestrate activities within a DevOps-oriented value stream.You'll start with an introduction to the concepts of delivering value and understand how VSM methods and tools support improved value delivery from a Lean production perspective. The book covers the complexities of implementing modern CI/CD and DevOps pipelines and then guides you through an eight-step VSM methodology with the help of a use case showing an Agile team's efforts to install a CI/CD pipeline. Free from marketing hype or vendor bias, this book presents the current VSM tool vendors and customer use cases that showcase their products' strengths. As you advance through the book, you'll learn four approaches to implementing a DevOps pipeline and get guidance on choosing the best fit.By the end of this VSM book, you'll be ready to develop and execute a plan to streamline your software delivery pipelines and improve your organization's value stream delivery.
Xamarin 4.x Cross-Platform Application Development. Click here to enter text. - Third Edition
Xamarin is a leading cross-platform application development tool used by top companies such as Coca-Cola, Honeywell, and Alaska Airlines to build apps. Version 4 features significant updates to the platform including the release of Xamarin.Forms 2.0 and improvements have been made to the iOS and Android designers. Xamarin was acquired by Microsoft so it is now a part of the Visual Studio family.This book will show you how to build applications for iOS, Android, and Windows. You will be walked through the process of creating an application that comes complete with a back-end web service and native features such as GPS location, camera, push notifications, and other core features. Additionally, you’ll learn how to use external libraries with Xamarin and Xamarin.Forms to create user interfaces. This book also provides instructions for Visual Studio and Windows. This edition has been updated with new screenshots and detailed steps to provide you with a holistic overview of the new features in Xamarin 4.
Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, ...
Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further, this is the course you need!In this course, we will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. You’ll then find your way around different data and numerical problems, get to grips with Spark and HDFS, and set up migration scripts for web mining. You’ll be able to quickly and accurately perform hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. Finally, you will delve into advanced techniques such as performing regression, quantifying cause and effect using Bayesian methods, and discovering how to use Python’s tools for supervised machine learning.The course provides you with highly practical content explaining data analysis with Python, from the following Packt books:1. Getting Started with Python Data Analysis.2. Python Data Analysis Cookbook.3. Mastering Python Data Analysis.By the end of this course, you will have all the knowledge you need to analyze your data with varying complexity levels, and turn it into actionable insights.
Desislav Andreev, Stanimir Lukanov, Milena Lazarova
Around 35 million Linux and almost 2 billion Android users rely on C++ for everything from the simplest embedded and IoT devices to cloud services, supercomputing, and space exploration. To help you produce high-quality software, two industry experts have transformed their knowledge and experience into practical examples in system programming with C++ Programming for Linux Systems.In this book, you'll explore the latest C++20 features, while working on multiple specific use cases. You’ll get familiar with the coroutines and modern approaches in concurrent and multithreaded programming. You'll also learn to reshape your thinking when analyzing system behavior in Linux (POSIX) environments. Additionally, you'll discover advanced discussions and novel solutions for complex challenges, while approaching trivial system operations with a new outlook and learning to choose the best design for your particular case.You can use this workbook as an introduction to system programming and software design in Linux or any Unix-based environment. You’ll also find it useful as a guideline or a supplement to any C++ book.By the end of this book, you’ll have gained advanced knowledge and skills for working with Linux or any Unix-based environment.
Aaron Jones, Christopher Kruger, Benjamin Johnston
Do you find it difficult to understand how popular companies like WhatsApp and Amazon find valuable insights from large amounts of unorganized data? The Unsupervised Learning Workshop will give you the confidence to deal with cluttered and unlabeled datasets, using unsupervised algorithms in an easy and interactive manner.The book starts by introducing the most popular clustering algorithms of unsupervised learning. You'll find out how hierarchical clustering differs from k-means, along with understanding how to apply DBSCAN to highly complex and noisy data. Moving ahead, you'll use autoencoders for efficient data encoding.As you progress, you’ll use t-SNE models to extract high-dimensional information into a lower dimension for better visualization, in addition to working with topic modeling for implementing natural language processing (NLP). In later chapters, you’ll find key relationships between customers and businesses using Market Basket Analysis, before going on to use Hotspot Analysis for estimating the population density of an area.By the end of this book, you’ll be equipped with the skills you need to apply unsupervised algorithms on cluttered datasets to find useful patterns and insights.