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This book describes cloud computing as a service that is "highly scalable" and operates in "a resilient environment". The authors emphasize architectural layers and models - but also business and security factors.
Well-known security experts decipher the most challenging aspect of cloud computing-security Cloud computing allows for both large and small organizations to have the opportunity to use Internet-based services so that they can reduce start-up costs, lower capital expenditures, use services on a pay-as-you-use basis, access applications only as needed, and quickly reduce or increase capacities. However, these benefits are accompanied by a myriad of security issues, and this valuable book tackles the most common security challenges that cloud computing faces. The authors offer you years of unparalleled expertise and knowledge as they discuss the extremely challenging topics of data ownership, privacy protections, data mobility, quality of service and service levels, bandwidth costs, data protection, and support. As the most current and complete guide to helping you find your way through a maze of security minefields, this book is mandatory reading if you are involved in any aspect of cloud computing. Coverage Includes: Cloud Computing Fundamentals Cloud Computing Architecture Cloud Computing Software Security Fundamentals Cloud Computing Risks Issues Cloud Computing Security Challenges Cloud Computing Security Architecture Cloud Computing Life Cycle Issues Useful Next Steps and Approaches
The Complete Guide to Human Resources and the Law will help you navigate complex and potentially costly Human Resources issues. You'll know what to do (and what not to do) to avoid costly mistakes or oversights, confront HR problems - legally and effectively - and understand the rules. The Complete Guide to Human Resources and the Law offers fast, dependable, plain English legal guidance for HR-related situations from ADA accommodation, diversity training, and privacy issues to hiring and termination, employee benefit plans, compensation, and recordkeeping. It brings you the most up-to-date information as well as practical tips and checklists in a well-organized, easy-to-use resource. The 2019 Edition provides new and expanded coverage of issues such as: The Supreme Court held in March 2016 that to prove damages in an Fair Labor Standards Act (FLSA) donning/doffing class action, an expert witness' testimony could be admitted Tyson Foods, Inc. v. Bouaphakeo, 136 S. Ct. 1036 (2016). Executive Order 13706, signed on Labor Day 2015, takes effect in 2017. It requires federal contractors to allow employees to accrue at least one hour of paid sick leave for every 30 hours they work, and unused sick leave can be carried over from year to year. Mid-2016 DOL regulations make millions more white-collar employees eligible for overtime pay, by greatly increasing the salary threshold for the white-collar exemption. Updates on the PATH Act (Protecting Americans From Tax Hikes; Pub. L. No. 114-113. The DOL published the "fiduciary rule" in final form in April 2016, with full compliance scheduled for January 1, 2018. The rule makes it clear that brokers who are paid to offer guidance on retirement accounts and Individual Retirement Arrangements (IRAs) are fiduciaries. In early 2016, the Equal Employment Opportunity Commission (EEOC) announced it would allow charging parties to request copies of the employer's position statement in response to the charge. The Supreme Court ruled that, in constructive discharge timing requirements run from the date the employee gives notice of his or her resignation--not the effective date of the resignation. Certiorari was granted to determine if the Federal Arbitration Act (FAA) preempts consideration of severing provisions for unconscionability. Previous Edition: Complete Guide to Human Resources and the Law, 2018 Edition ISBN 9781454884309
With their rapidly changing architecture and API-driven automation, cloud platforms come with unique security challenges and opportunities. This hands-on book guides you through security best practices for multivendor cloud environments, whether your company plans to move legacy on-premises projects to the cloud or build a new infrastructure from the ground up. Developers, IT architects, and security professionals will learn cloud-specific techniques for securing popular cloud platforms such as Amazon Web Services, Microsoft Azure, and IBM Cloud. Chris Dotson—an IBM senior technical staff member—shows you how to establish data asset management, identity and access management, vulnerability management, network security, and incident response in your cloud environment.
New edition of the bestselling guide to Mastering Windows Server, updated to Windows Server 2022 with improved security, better platform flexibility, new windows admin center, upgraded Hyper-V manager and hybrid cloud support Key Features Develop necessary skills to design and implement Microsoft Server 2019 in enterprise environment Provide support to your medium to large enterprise and leverage your experience in administering Microsoft Server 2019 Effectively administering Windows server 2019 with the help of practical examples Book DescriptionMastering Windows Server 2019 – Second Edition covers all of the essential information needed to implement and utilize this latest-and-greatest platform as the core of your data center computing needs. You will begin by installing and managing Windows Server 2019, and by clearing up common points of confusion surrounding the versions and licensing of this new product. Centralized management, monitoring, and configuration of servers is key to an efficient IT department, and you will discover multiple methods for quickly managing all of your servers from a single pane of glass. To this end, you will spend time inside Server Manager, PowerShell, and even the new Windows Admin Center, formerly known as Project Honolulu. Even though this book is focused on Windows Server 2019 LTSC, we will still discuss containers and Nano Server, which are more commonly related to the SAC channel of the server platform, for a well-rounded exposition of all aspects of using Windows Server in your environment. We also discuss the various remote access technologies available in this operating system, as well as guidelines for virtualizing your data center with Hyper-V. By the end of this book, you will have all the ammunition required to start planning for, implementing, and managing Windows.What you will learn Work with the updated Windows Server 2019 interface, including Server Core and Windows Admin Center Secure your network and data with new technologies in Windows Server 2019 Learn about containers and understand the appropriate situations to use Nano Server Discover new ways to integrate your data center with Microsoft Azure Harden your Windows Servers to help keep the bad guys out Virtualize your data center with Hyper-V Who this book is for If you are a System Administrator or an IT professional interested in designing and deploying Windows Server 2019 then this book is for you. Previous experience of Windows Server operating systems and familiarity with networking concepts is required.
Why you need this PMP guide: • Coverage of the 100% of the exam content • Lots of figures and tables for faster preparation • ITTO-made-easy with diagrams and built-in text • Simple explanations for difficult concepts • Synopsis and formulas section … for reference before the PMP exam • Easy-to-follow layout • 400+ sample questions with detailed explanations • Full-length practice exam • Tips for practical project management • How-to for Microsoft Project (MPP) application This book is a must-have for those preparing for PMP certification. It is different than existing books because we believe that PMP preparation can be quick and efficient. We have read the existing books and taken the PMP exam and we have found that most books contain unnecessary content. • Reduce your preparation time: There are several books in the market that have pages of painful and irrelevant text that would just be a waste of your time. This book has text that is concise and relevant for the exam. • Figures and tables: There are 200+ figures and tables in the book. When text is needed to explain the figure, the text is embedded into the figure, rather than forcing you to read long paragraphs and pages of commentary to find relevant material. • Personalized, conversational style: When possible, we use conversational style to make for easier reading. • Active learning: We believe that learning is best when the reader is involved (instead of doing a show and tell). Wherever applicable (e.g. for schedule, cost, quality, risk, procurement), there are workbook-style exercises. • Examples: You will find lots of examples followed by its underlying concept or generalized step-by-step procedure. This sequence makes it easier to understand concepts. REVIEW FROM CONTACT 1: I have studied various PMP guides and tutorials in the market. But this book is different, stands outs and would be the best companion guide to the PMBOK. Difficult concepts are presented in a style that is easy to follow. The content is concise and supported by illustrative figures and tables. This will save you from wasting your time on irrelevant or copious content. In my opinion, this is the ONLY book you will need to pass the PMP exam. Other printed books and online sites have questions that are easier than the PMP exam and some wrong and answers and explanations. The 400+ questions are at the same level of rigor as you will find in the PMP exam. I wish I had this guide when I prepared for the PMP exam. - Andrew Anderson, PMP, Los Angeles, CA
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.
This book critically evaluates the EU regulatory framework for the liability of host Internet Service Providers (ISPs) for copyright and trade mark infringements and provides a cluster of novel recommendations for its improvement. The book recommends the imposition of a duty of care to host ISPs to curb the dissemination of unauthorised works and counterfeit goods, the ascription of a transparency obligation to host ISPs towards their users, and the establishment of a supervisory authority for host ISPs. Host ISPs have facilitated the dissemination of content amongst users and the purchase of goods online, enabling copyright holders and brand owners to attract a greater audience for their works and goods. However, their services have attracted a high number of copyright and trade mark violations, too. Neither Article 14 of the e-Commerce Directive nor Article 17 of the Copyright in the Digital Single Market Directive provide a solid response to the issue of host ISPs' liability. This book is a valuable resource for researchers in IT and IP law and offers a new perspective for resolving online IP disputes.
Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers
Cloud computing-accessing computing resources over the Internet-is rapidly changing the landscape of information technology. Its primary benefits compared to on-premise computing models are reduced costs and increased agility and scalability. Hence, cloud computing is receiving considerable interest among several stakeholders-businesses, the IT ind