Видавець: Packt Publishing
Chris Dent
Mastering PowerShell Scripting, Fifth Edition, is your comprehensive guide to harnessing PowerShell’s full potential. This edition introduces new chapters on debugging, troubleshooting, and creating GUIs while covering the latest enhancements in PowerShell 7.3, including parameters, objects, and .NET classes.The book takes you from foundational concepts to advanced techniques, covering asynchronous processing, desired state configuration, and managing large datasets. You'll explore PowerShell’s automation features, error-handling strategies, and integration with external services. Additionally, this guide provides practical insights into working with regular expressions, Windows Management Instrumentation, and complex scripting methods.By the end of this book, you’ll have the skills to efficiently automate tasks, troubleshoot scripts, and leverage PowerShell’s advanced capabilities for real-world scenarios.Be sure to explore the online bonus chapters 8, 9, and 20, where we dive into Strings, Numbers, and Dates, Regular Expressions, and Building Modules.
Joseph Babcock
The volume, diversity, and speed of data available has never been greater. Powerful machine learning methods can unlock the value in this information by finding complex relationships and unanticipated trends. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications to deliver insights that are of tremendous value to their organizations. In Mastering Predictive Analytics with Python, you will learn the process of turning raw data into powerful insights. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications and how to quickly apply these methods to your own data to create robust and scalable prediction services.Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates not only how these methods work, but how to implement them in practice. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring the insights of predictive modeling to life
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.
James D. Miller , Rui Miguel Forte
R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks.By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R.
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.
Russell Anderson-Williams
Prezi is a tool for delivering presentations in a linear or non-linear format. This cloud-based software enables users to structure presentations on an infinite canvass in a way that is much more engaging and visually stimulating to the audience.Mastering Prezi for Business Presentations is a must read for anyone already using Prezi who wants to take their presentations to the next level. It covers all of the technical elements of the software, whilst also looking at the practicalities of using Prezi in a business environment.This book covers all the technical elements of Prezi and also teaches the reader how to think for Prezi, and approach their design in the best way. This is an essential resource for people who want to use Prezi seriously.As well as covering best practices for inserting imagery, sound, and video, this book also covers topics for business users like collaborating and sharing Prezis online, using Prezi at a meeting to brain storm with overseas colleagues, and how to 'Prezify' PowerPoint or Keynote slides.Mastering Prezi for Business Presentations will escalate you from Prezi user to master with ease.
Russell Anderson-Williams, John J Sylvia IV
If you use Prezi in business and want to take your presentations to the next level, or if you want to become the office Prezi master, this book is for you.
Ankur Ankan
Probabilistic Graphical Models is a technique in machine learning that uses the concepts of graph theory to compactly represent and optimally predict values in our data problems. In real world problems, it's often difficult to select the appropriate graphical model as well as the appropriate inference algorithm, which can make a huge difference in computation time and accuracy. Thus, it is crucial to know the working details of these algorithms.This book starts with the basics of probability theory and graph theory, then goes on to discuss various models and inference algorithms. All the different types of models are discussed along with code examples to create and modify them, and also to run different inference algorithms on them. There is a complete chapter devoted to the most widely used networks Naive Bayes Model and Hidden Markov Models (HMMs). These models have been thoroughly discussed using real-world examples.
Edward Unger, Ryan Coyne
Do you want to start a business or turn a hobby into a profession, but feel like you're running out of time? Do you want to become a productivity powerhouse, effectively juggling personal and professional responsibilities? Does your team need help boosting efficiency? This comprehensive guide provides practical strategies and action plans to optimize your work and home life using ClickUp.Achieve project success by setting meaningful KPIs, creating team dashboards, generating real-time reports, and extending ClickUp with integrations. You’ll learn how to implement and optimize your workspace structure, project management, processes, workflows, automation, AI, and how to use ClickUp Brain as a knowledgebase. This book also helps you master ClickUp for home life by using it to manage personal tasks, plan vacations, collaborate on projects, maintain interactive inventory, and track household chores. Finally, you'll explore advanced features, goal setting, and personal approaches to maximize your leverage of ClickUp as your 'accomplishment system.Whether you're a seasoned user or just getting started, this ClickUp handbook provides best practices and highlights common mistakes for implementing and optimizing ClickUp to unlock its potential and achieve your goals.
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.
Wasim Ahmed
Proxmox is an open source server virtualization solution that has enterprise-class features to manage virtual machines, to be used for storage, and to virtualize both Linux and Windows application workloads.You begin with refresher on the advanced installation features and the Proxmox GUI to familiarize yourself with the Proxmox VE hypervisor. You then move on to explore Proxmox under the hood, focusing on the storage systems used with Proxmox. Moving on, you will learn to manage KVM Virtual Machines and Linux Containers and see how networking is handled in Proxmox. You will then learn how to protect a cluster or a VM with a firewall and explore the new HA features introduced in Proxmox VE 4 along with the brand new HA simulator. Next, you will dive deeper into the backup/restore strategy followed by learning how to properly update and upgrade a Proxmox node. Later, you will learn how to monitor a Proxmox cluster and all of its components using Zabbix. By the end of the book, you will become an expert at making Proxmox environments work in production environments with minimum downtime.
Mastering Puppet 5. Optimize enterprise-grade environment performance with Puppet
Ryan Russell-Yates, Jason Southgate
Puppet is a configuration management system and a language written for and by system administrators to manage a large number of systems efficiently and prevent configuration drift.The core topics this book addresses are Puppet's latest features and mastering Puppet Enterprise. You will begin by writing a new Puppet module, gaining an understanding of the guidelines and style of the Puppet community. Following on from this, you will take advantage of the roles and profiles pattern, and you will learn how to structure your code. Next, you will learn how to extend Puppet and write custom facts, functions, types, and providers in Ruby, and also use the new features of Hiera 5. You will also learn how to configure the new Code Manager component, and how to ensure code is automatically deployed to (multiple) Puppet servers. Next, you will learn how to integrate Puppet with Jenkins and Git to build an effective workflow for multiple teams, and use the new Puppet Tasks feature and the latest Puppet Orchestrator language extensions. Finally, you will learn how to scale and troubleshoot Puppet.By the end of the book, you will be able to deal with problems of scale and exceptions in your code, automate workflows, and support multiple developers working simultaneously.
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.
Thomas Uphill
Presented in an easy-to-follow, step-by-step tutorial format and packed with examples, this book will lead you through making the best out of Puppet in an enterprise environment. If you are a system administrator or developer who has used Puppet in production and are looking for ways to easily use Puppet in an enterprise environment, this book is for you. This book assumes an intermediate knowledge of Puppet and is intended for those writing modules or deploying Puppet in an enterprise environment.
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
Magnus Vilhelm Persson, Luiz Felipe Martins
Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? Well, look no further, this is the book you want!Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You’ll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making.You’ll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you’ll move on to review statistical inference using Python, Pandas, and SciPy. After that, we’ll focus on performing regression using computational tools and you’ll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you’ll discover how to use Python’s tools for supervised machine learning.
Kirthi Raman
Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences.This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis.By the end of this book, you will be able to effectively solve a broad set of data analysis problems.
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.