Programowanie
Rui Miguel Forte
This book is intended for the budding data scientist, predictive modeler, or quantitative analyst with only a basic exposure to R and statistics. It is also designed to be a reference for experienced professionals wanting to brush up on the details of a particular type of predictive model. Mastering Predictive Analytics with R assumes familiarity with only the fundamentals of R, such as the main data types, simple functions, and how to move data around. No prior experience with machine learning or predictive modeling is assumed, however you should have a basic understanding of statistics and calculus at a high school level.
Alvaro Fuentes
Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics.By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysis.
William Hegedus
With growing focus on observability and reliability, establishing a scalable and reliable monitoring environment is more important than ever. Over the last decade, Prometheus has emerged as the leading open-source, time-series based monitoring software catering to this demand. Written by an open-source advocate and Prometheus contributor, this guide provides an in-depth look at Prometheus, covering best practices and offering insights into scaling, operating, and extending Prometheus, from small on-premises workloads to multi-cloud, globally distributed environments.The book helps you revisit the basics of Prometheus, before moving on to advanced techniques of observability and monitoring using Prometheus. You’ll find out how to deploy Prometheus on Kubernetes and achieve an HA alerting infrastructure in Prometheus. You’ll also learn to leverage Prometheus in your daily operations through alerts, Grafana dashboards, and building your own exporter. Finally, you’ll explore various open-source projects that extend the functionality of Prometheus, help with various aspects of running Prometheus at scale, and make the most of Prometheus data.By the end of this book, you’ll be able to confidently build, automate, and deliver your infrastructure and CI/CD pipelines in cloud-based applications.
William Hegedus
With growing focus on observability and reliability, establishing a scalable and reliable monitoring environment is more important than ever. Over the last decade, Prometheus has emerged as the leading open-source, time-series based monitoring software catering to this demand. Written by an open-source advocate and Prometheus contributor, this guide provides an in-depth look at Prometheus, covering best practices and offering insights into scaling, operating, and extending Prometheus, from small on-premises workloads to multi-cloud, globally distributed environments.The book helps you revisit the basics of Prometheus, before moving on to advanced techniques of observability and monitoring using Prometheus. You’ll find out how to deploy Prometheus on Kubernetes and achieve an HA alerting infrastructure in Prometheus. You’ll also learn to leverage Prometheus in your daily operations through alerts, Grafana dashboards, and building your own exporter. Finally, you’ll explore various open-source projects that extend the functionality of Prometheus, help with various aspects of running Prometheus at scale, and make the most of Prometheus data.By the end of this book, you’ll be able to confidently build, automate, and deliver your infrastructure and CI/CD pipelines in cloud-based applications.
Mastering Proxmox. Build virtualized environments using the Proxmox VE hypervisor - Third Edition
Wasim Ahmed
Proxmox is an open source server virtualization solution that has enterprise-class features for managing virtual machines, for storage, and to virtualize both Linux and Windows application workloads.You'll begin with a refresher on the advanced installation features and the Proxmox GUI to familiarize yourself with the Proxmox VE hypervisor. Then, you'll move on to explore Proxmox under the hood, focusing on storage systems, such as Ceph, used with Proxmox. Moving on, you'll learn to manage KVM virtual machines, deploy Linux containers fast, and see how networking is handled in Proxmox. You'll also learn how to protect a cluster or a VM with a firewall and explore the new high availability features introduced in Proxmox VE 5.0. Next, you'll dive deeper into the backup/restore strategy and see how to properly update and upgrade a Proxmox node. Later, you'll learn how to monitor a Proxmox cluster and all of its components using Zabbix. Finally, you'll discover how to recover Promox from disaster strikes through some real-world examples. By the end of the book, you'll be an expert at making Proxmox work in production environments with minimal downtime.
Wasim Ahmed
This is not an instructional guide, but a practical, scenario-based book which guides you through everything you need to know in a practical manner by letting you build your own cluster. By the end of the book, you will have a fully functional Proxmox cluster setup at your disposal and have the knowledge to replicate virtualization solutions .If you already know what the word virtualization means and you are ready to stand out from the crowd equipped with the unique ability to design and implement a rock-solid virtualized network environment using Proxmox, then you have just picked up the only book you will need. Linux system administration experience together with knowledge of networking and virtualization concepts is assumed. This book is also useful if you are already using Proxmox and simply want to master its advanced features.
Thomas Uphill
Puppet is a configuration management system and a language. It was written for and by system administrators to manage large numbers of systems efficiently and prevent configuration drifts.Mastering Puppet deals with the issues faced when scaling out Puppet to handle large numbers of nodes. It will show you how to fit Puppet into your enterprise and allow many developers to work on your Puppet code simultaneously. In addition, you will learn to write custom facts and roll your own modules to solve problems. Next, popular options for performing reporting and orchestration tasks will be introduced in this book. Moving over to troubleshooting techniques, which will be very useful. The concepts presented are useful to any size organization. By the end of the book, you will know how to deal with problems of scale and exceptions in your code, automate workflows, and support multiple developers working simultaneously.
Mastering PyCharm. Use PyCharm with fluid efficiency to write idiomatic python code
Nafiul Islam
PyCharm is addictive, with powerful and configurable code completion, superb editing tools, top-notch support, diverse plugins, and a vibrant ecosystem to boot. Learning how PyCharm works and maximising the synergy of its powerful tools will help you to rapidly develop applications.From leveraging the power of the editor to understanding PyCharm's internals, this book will give you a comprehensive view of PyCharm and allow you to make your own choices about which workflow and tools are best for you.You will start by getting comfortable with PyCharm and making it look exactly like you want. You can customize the tools and taskbars to suit individual developers' coding styles. You also learn how to assign keyboard shortcuts. You will master debugging by inserting breakpoints, collecting runtime data, and debugging from the console. You will understand how PyCharm works underneath and how plugins such as Codemap, Vim, Bitbucket, Assets compressor, markdown, bash file, shortcut translator, and .gitignore leverage the power of the IntelliJ platform.You will become comfortable using the VCS interface in PyCharm and see the benefits of using it for some simple tasks as well as some more complex tasks such as partial commits using changelists.You will take an in-depth look at the various tools in PyCharm, improving your workflow drastically. Finally, you will deploy powerful PyCharm tools for Django, Flask, GAE, and Pyramid Development, becoming well acquainted with PyCharm’s toolset for web development with popular platforms.Packed with insider tricks, this book will help you boost productivity with PyCharm.
Rick Hattem
Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10.Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community.If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Kamon Ayeva, Sakis Kasampalis
Python is an object-oriented scripting language that is used in a wide range of categories. In software engineering, a design pattern is an elected solution for solving software design problems. Although they have been around for a while, design patterns remain one of the top topics in software engineering, and are a ready source for software developers to solve the problems they face on a regular basis. This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications. By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size.
Kamon Ayeva, Sakis Kasampalis
Python is an object-oriented scripting language that is used in a wide range of categories. In software engineering, a design pattern is an elected solution for solving software design problems. Although they have been around for a while, design patterns remain one of the top topics in software engineering, and are a ready source for software developers to solve the problems they face on a regular basis. This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications. By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size.
Kamon Ayeva, Sakis Kasampalis
As software systems become increasingly complex, maintaining code quality, scalability, and efficiency can be a daunting challenge. Mastering Python Design Patterns is an essential resource that equips you with the tools you need to overcome these hurdles and create robust, scalable applications.The book delves into design principles and patterns in Python, covering both classic and modern patterns, and apply them to solve daily challenges as a Python developer or architect.Co-authored by two Python experts with a combined experience of three decades, this new edition covers creational, structural, behavioral, and architectural patterns, including concurrency, asynchronous, and performance patterns. You'll find out how these patterns are relevant to various domains, such as event handling, concurrency, distributed systems, and testing. Whether you're working on user interfaces (UIs), web apps, APIs, data pipelines, or AI models, this book equips you with the knowledge to build robust and maintainable software. The book also presents Python anti-patterns, helping you avoid common pitfalls and ensuring your code remains clean and efficient.By the end of this book, you'll be able to confidently apply classic and modern Python design patterns to build robust, scalable applications.
Sakis Kasampalis
This book is for Python programmers with an intermediate background and an interest in design patterns implemented in idiomatic Python. Programmers of other languages who are interested in Python can also benefit from this book, but it would be better if they first read some introductory materials that explain how things are done in Python.
Samir Madhavan
Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving.This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science.Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods.Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics.
James Ma Weiming
The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples.You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and scikit-learn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance.By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis.
James Ma Weiming
If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.
José Manuel Ortega
It’s becoming more and more apparent that security is a critical aspect of IT infrastructure. A data breach is a major security incident, usually carried out by just hacking a simple network line. Increasing your network’s security helps step up your defenses against cyber attacks. Meanwhile, Python is being used for increasingly advanced tasks, with the latest update introducing many new packages. This book focuses on leveraging these updated packages to build a secure network with the help of Python scripting. This book covers topics from building a network to the different procedures you need to follow to secure it. You’ll first be introduced to different packages and libraries, before moving on to different ways to build a network with the help of Python scripting. Later, you will learn how to check a network’s vulnerability using Python security scripting, and understand how to check vulnerabilities in your network. As you progress through the chapters, you will also learn how to achieve endpoint protection by leveraging Python packages along with writing forensic scripts. By the end of this book, you will be able to get the most out of the Python language to build secure and robust networks that are resilient to attacks.
José Manuel Ortega
It’s now more apparent than ever that security is a critical aspect of IT infrastructure, and that devastating data breaches can occur from simple network line hacks. As shown in this book, combining the latest version of Python with an increased focus on network security can help you to level up your defenses against cyber attacks and cyber threats.Python is being used for increasingly advanced tasks, with the latest update introducing new libraries and packages featured in the Python 3.7.4 recommended version. Moreover, most scripts are compatible with the latest versions of Python and can also be executed in a virtual environment.This book will guide you through using these updated packages to build a secure network with the help of Python scripting. You’ll cover a range of topics, from building a network to the procedures you need to follow to secure it. Starting by exploring different packages and libraries, you’ll learn about various ways to build a network and connect with the Tor network through Python scripting. You will also learn how to assess a network's vulnerabilities using Python security scripting. Later, you’ll learn how to achieve endpoint protection by leveraging Python packages, along with writing forensic scripts.By the end of this Python book, you’ll be able to use Python to build secure apps using cryptography and steganography techniques.