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Titre : Increasing Autodesk Revit Productivity for BIM Projects Type de document : e-book Auteurs : Fabio ROBERTI Editeur : PACKT PUBLISHING Année de publication : 2021 ISBN/ISSN/EAN : 9781800566804 Note générale : copyrighted Langues : Anglais (eng) Résumé : Discover how to implement Revit best practices along with Dynamo and Power BI to visualize and analyze BIM informationKey FeaturesBoost productivity in Revit and apply multiple workflows to work efficiently on BIM projectsOptimize your daily work in Revit to perform more tasks in less timeTake a hands-on approach to improving your efficiency with useful explanations, which will step-change your productivityBook DescriptionRevit software helps architects, BIM coordinators, and BIM managers to create BIM models and analyze data to improve design and construction. Building Information Modeling (BIM) has promoted a transformation in the engineering and construction industries where information is at the core of a methodology that improves productivity, providing several benefits in comparison to the traditional 2D CAD process. This book takes a hands-on approach to implementing this new methodology effectively. Complete with step-by-step explanations of essential concepts and practical examples, this Revit book begins by explaining the principles of productivity in Revit and data management for BIM projects. You'll get to grips with the primary BIM documentation to start a BIM project, including the contract, Exchange Information Requirements (EIR), and BIM Execution Plan (BEP/BXP). Later, you'll create a Revit template, start a Revit project, and explore the core functionalities of Revit to increase productivity. Once you've built the foundation, you'll learn about Revit plugins and use Dynamo for visual programming and Power BI for analyzing BIM information. By the end of this book, you'll have a solid understanding of Revit as construction and design software, how to increase productivity in Revit, and how to apply multiple workflows in your project to manage BIM.What you will learnExplore the primary BIM documentation to start a BIM projectSet up a Revit project and apply the correct coordinate system to ensure long-term productivityImprove the efficiency of Revit core functionalities that apply to daily activitiesUse visual programming with Dynamo to boost productivity and manage data in BIM projectsImport data from Revit to Power BI and create project dashboards to analyze dataDiscover the different Revit plugins for improved productivity, visualization, and analysisImplement best practices for modeling in RevitWho this book is forThis book is for architects, designers, engineers, modelers, BIM coordinators, and BIM managers interested in learning Autodesk Revit best practices. Increasing Autodesk Revit Productivity for BIM Projects will help you to explore the methodology that combines information management and research for quality inputs when working in Revit. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88916219 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=535490 Industrial Cybersecurity : Efficiently monitor the cybersecurity posture of your ICS environment Ed. 2 / Pascal ACKERMAN / PACKT PUBLISHING (2021)
Titre : Industrial Cybersecurity : Efficiently monitor the cybersecurity posture of your ICS environment Ed. 2 Type de document : e-book Auteurs : Pascal ACKERMAN Editeur : PACKT PUBLISHING Année de publication : 2021 ISBN/ISSN/EAN : 9781800202092 Note générale : copyrighted Langues : Anglais (eng) Résumé : Get up and running with industrial cybersecurity monitoring with this hands-on book, and explore ICS cybersecurity monitoring tasks, activities, tools, and best practices Key Features Architect, design, and build ICS networks with security in mind Perform a variety of security assessments, checks, and verifications Ensure that your security processes are effective, complete, and relevant Book Description With Industrial Control Systems (ICS) expanding into traditional IT space and even into the cloud, the attack surface of ICS environments has increased significantly, making it crucial to recognize your ICS vulnerabilities and implement advanced techniques for monitoring and defending against rapidly evolving cyber threats to critical infrastructure. This second edition covers the updated Industrial Demilitarized Zone (IDMZ) architecture and shows you how to implement, verify, and monitor a holistic security program for your ICS environment. You'll begin by learning how to design security-oriented architecture that allows you to implement the tools, techniques, and activities covered in this book effectively and easily. You'll get to grips with the monitoring, tracking, and trending (visualizing) and procedures of ICS cybersecurity risks as well as understand the overall security program and posture/hygiene of the ICS environment. The book then introduces you to threat hunting principles, tools, and techniques to help you identify malicious activity successfully. Finally, you'll work with incident response and incident recovery tools and techniques in an ICS environment. By the end of this book, you'll have gained a solid understanding of industrial cybersecurity monitoring, assessments, incident response activities, as well as threat hunting. What you will learn Monitor the ICS security posture actively as well as passively Respond to incidents in a controlled and standard way Understand what incident response activities are required in your ICS environment Perform threat-hunting exercises using the Elasticsearch, Logstash, and Kibana (ELK) stack Assess the overall effectiveness of your ICS cybersecurity program Discover tools, techniques, methodologies, and activities to perform risk assessments for your ICS environment Who this book is for If you are an ICS security professional or anyone curious about ICS cybersecurity for extending, improving, monitoring, and validating your ICS cybersecurity posture, then this book is for you. IT/OT professionals interested in entering the ICS cybersecurity monitoring domain or searching for additional learning material for different industry-leading cybersecurity certifications will also find this book useful. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88947473 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=581313
Titre : Infrastructure Monitoring with Amazon CloudWatch Type de document : e-book Auteurs : Ewere DIAGBOYA Editeur : PACKT PUBLISHING Année de publication : 2021 ISBN/ISSN/EAN : 9781800566057 Note générale : copyrighted Langues : Anglais (eng) Résumé : Explore real-world examples of issues with systems and find ways to resolve them using Amazon CloudWatch as a monitoring serviceKey FeaturesBecome well-versed with monitoring fundamentals such as understanding the building blocks and architecture of networkingLearn how to ensure your applications never face downtimeGet hands-on with observing serverless applications and servicesBook DescriptionCloudWatch is Amazon's monitoring and observability service, designed to help those in the IT industry who are interested in optimizing resource utilization, visualizing operational health, and eventually increasing infrastructure performance. This book helps IT administrators, DevOps engineers, network engineers, and solutions architects to make optimum use of this cloud service for effective infrastructure productivity. You'll start with a brief introduction to monitoring and Amazon CloudWatch and its core functionalities. Next, you'll get to grips with CloudWatch features and their usability. Once the book has helped you develop your foundational knowledge of CloudWatch, you'll be able to build your practical skills in monitoring and alerting various Amazon Web Services, such as EC2, EBS, RDS, ECS, EKS, DynamoDB, AWS Lambda, and ELB, with the help of real-world use cases. As you progress, you'll also learn how to use CloudWatch to detect anomalous behavior, set alarms, visualize logs and metrics, define automated actions, and rapidly troubleshoot issues. Finally, the book will take you through monitoring AWS billing and costs. By the end of this book, you'll be capable of making decisions that enhance your infrastructure performance and maintain it at its peak.What you will learnUnderstand the meaning and importance of monitoringExplore the components of a basic monitoring systemUnderstand the functions of CloudWatch Logs, metrics, and dashboardsDiscover how to collect different types of metrics from EC2Configure Amazon EventBridge to integrate with different AWS servicesGet up to speed with the fundamentals of observability and the AWS services used for observabilityFind out about the role Infrastructure As Code (IaC) plays in monitoringGain insights into how billing works using different CloudWatch featuresWho this book is forThis book is for developers, DevOps engineers, site reliability engineers, or any IT individual with hands-on intermediate-level experience in networking, cloud computing, and infrastructure management. A beginner-level understanding of AWS and application monitoring will also be helpful to grasp the concepts covered in the book more effectively. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88913048 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=534755
Titre : Interactive Dashboards and Data Apps with Plotly and Dash Type de document : e-book Auteurs : Elias DABBAS Editeur : PACKT PUBLISHING Année de publication : 2021 ISBN/ISSN/EAN : 9781800568914 Note générale : copyrighted Langues : Anglais (eng) Résumé : Learn how to build web-based and mobile-friendly analytic apps and interactive dashboards with PythonKey FeaturesDevelop data apps and dashboards without any knowledge of JavaScriptMap different types of data such as integers, floats, and dates to bar charts, scatter plots, and moreCreate controls and visual elements with multiple inputs and outputs and add functionality to the app as per your requirementsBook DescriptionWith Plotly's Dash framework, it is now easier than ever for Python programmers to develop complete data apps and interactive dashboards. Dash apps can be used by a non-technical audience, and this will make data analysis accessible to a much wider group of people. This book will help you to explore the functionalities of Dash for visualizing data in different ways and getting the most out of it. The book starts with an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it. Next, you'll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them. By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.What you will learnFind out how to run a fully interactive and easy-to-use appConvert your charts to various formats including images and HTML filesUse Plotly Express and the grammar of graphics for easily mapping data to various visual attributesCreate different chart types, such as bar charts, scatter plots, histograms, maps, and moreExpand your app by creating dynamic pages that generate content based on URLsImplement new callbacks to manage charts based on URLs and vice versaWho this book is forThis Plotly Dash book is for data professionals and data analysts who want to gain a better understanding of their data with the help of different visualizations and dashboards. Basic to intermediate-level knowledge of the Python programming language will help you to grasp the concepts covered in this book more effectively. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88916186 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=535733
Titre : Interpretable Machine Learning with Python Type de document : e-book Auteurs : Serg MASIS Editeur : PACKT PUBLISHING Année de publication : 2021 ISBN/ISSN/EAN : 9781800203907 Note générale : copyrighted Langues : Anglais (eng) Résumé : Understand the key aspects and challenges of machine learning interpretability, learn how to overcome them with interpretation methods, and leverage them to build fairer, safer, and more reliable modelsKey FeaturesLearn how to extract easy-to-understand insights from any machine learning modelBecome well-versed with interpretability techniques to build fairer, safer, and more reliable modelsMitigate risks in AI systems before they have broader implications by learning how to debug black-box modelsBook DescriptionDo you want to understand your models and mitigate risks associated with poor predictions using machine learning (ML) interpretation? Interpretable Machine Learning with Python can help you work effectively with ML models. The first section of the book is a beginner's guide to interpretability, covering its relevance in business and exploring its key aspects and challenges. You'll focus on how white-box models work, compare them to black-box and glass-box models, and examine their trade-off. The second section will 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, the book also helps the reader to interpret model outcomes using examples. In the third section, 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.What you will learnRecognize the importance of interpretability in businessStudy models that are intrinsically interpretable such as linear models, decision trees, and Naive BayesBecome well-versed in interpreting models with model-agnostic methodsVisualize how an image classifier works and what it learnsUnderstand how to mitigate the influence of bias in datasetsDiscover how to make models more reliable with adversarial robustnessUse monotonic constraints to make fairer and safer modelsWho this book is forThis book is for data scientists, machine learning developers, and data stewards who have an increasingly critical responsibility to explain how the AI systems they develop work, their impact on decision making, and how they identify and manage bias. Working knowledge of machine learning and the Python programming language is expected. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88911892 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=534250 JavaScript from Beginner to Professional : Learn JavaScript quickly by building fun, interactive, and dynamic web apps, games, and pages / Laurence Lars SVEKIS / PACKT PUBLISHING (2021)PermalinkPermalinkPermalinkPermalinkPermalinkLaTeX Beginner's Guide : Create visually appealing texts, articles, and books for business and science using LaTeX / Stefan KOTTWITZ / PACKT PUBLISHING (2021)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkLearn Robotics Programming : Build and control AI-enabled autonomous robots using the Raspberry Pi and Python Ed. 2 / Danny STAPLE / PACKT PUBLISHING (2021)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkLLVM Techniques, Tips, and Best Practices Clang and Middle-End Libraries / Min-Yih HSU / PACKT PUBLISHING (2021)PermalinkMachine Learning Automation with TPOT : Build, validate, and deploy fully automated machine learning models with Python / Dario RADECIC / PACKT PUBLISHING (2021)Permalink
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