Windows 10 for Enterprise Administrators. Modern Administrators’ guide based on Redstone 3 version

Richard Diver, Manuel Singer, Jeff Stokes

Microsoft's launch of Windows 10 is a step toward satisfying enterprise administrators' needs for management and user experience customization. This book provides enterprise administrators with the knowledge needed to fully utilize the advanced feature set of Windows 10 Enterprise.This practical guide shows Windows 10 from an administrator's point of view. You'll focus on areas such as installation and configuration techniques based on your enterprise requirements, various deployment scenarios and management strategies, and setting up and managing admin and other user accounts. You'll see how to configure Remote Server Administration Tools to remotely manage Windows Server and Azure Active Directory. Lastly, you will learn modern mobile device management for effective BYOD and how to enable enhanced data protection, system hardening, and enterprise-level security with the new Windows 10 in order to prevent data breaches and to impede attacks.By the end of this book, you will know the key technologies and capabilities in Windows 10 and will confidently be able to manage and deploy these features in your organization.

Learning PySpark. Click here to enter text

Tomasz Drabas, Denny Lee

Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.

CompTIA Project+ Certification Guide. Learn project management best practices and successfully pass the CompTIA Project+ PK0-004 exam

J. Ashley Hunt

The CompTIA Project+ exam is designed for IT professionals who want to improve their career trajectory by gaining certification in project management specific to their industry. This guide covers everything necessary to pass the current iteration of the Project+ PK0-004 exam.The CompTIA Project+ Certification Guide starts by covering project initiation best practices, including an understanding of organizational structures, team roles, and responsibilities. You’ll then study best practices for developing a project charter and the scope of work to produce deliverables necessary to obtain formal approval of the end result. The ability to monitor your project work and make changes as necessary to bring performance back in line with the plan is the difference between a successful and unsuccessful project. The concluding chapters of the book provide best practices to help keep an eye on your projects and close them out successfully. The guide also includes practice questions created to mirror the exam experience and help solidify your understanding of core project management concepts.By the end of this book, you will be able to develop creative solutions for complex issues faced in project management.

Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics

Rich Collier, Bahaaldine Azarmi

Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data.As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure.By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly.

Become a Python Data Analyst. Perform exploratory data analysis and gain insight into scientific computing using Python

Alvaro Fuentes

Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations.Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations.In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques.By the end of this book, you will have hands-on experience performing data analysis with Python.

AMP: Building Accelerated Mobile Pages. Create lightning-fast mobile pages by leveraging AMP technology

Ruadhan O'Donoghue

Google introduced the Accelerated Mobile Pages (AMP) project to give mobile users lightning-fast response times when accessing web pages on mobile devices. AMP delivers great user experiences by providing a framework for optimizing web pages that otherwise would take much longer to load on a mobile platform.This book shows how to solve page performance issues using the mobile web technologies available today. You will learn how to build instant-loading web pages, and have them featured more prominently on Google searches. If you want your website to succeed on mobile, if you care about SEO, and if you want to stay competitive, then this book is for you! You will go on a mobile web development journey that demonstrates with concrete examples how to build lightning-fast pages that will keep your visitors on-site and happy. This journey begins by showing how to build a simple blog article-style web page using AMP. As new concepts are introduced this page is gradually refined until you will have the skills and confidence to build a variety of rich and interactive mobile web pages. These will include e-commerce product pages, interactive forms and menus, maps and commenting systems, and even Progressive Web Apps.

Data Analysis with Python. A Modern Approach

David Taieb

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects.Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.

Exploring Experience Design. Fusing business, tech, and design to shape customer engagement

Ezra Schwartz

We live in an experience economy in which interaction with products is valued more than owning them. Products are expected to engage and delight in order to form the emotional bonds that forge long-term customer loyalty:Products need to anticipate our needs and perform tasks for us: refrigerators order food, homes monitor energy, and cars drive autonomously; they track our vitals, sleep, location, finances, interactions, and content use; recognize our biometric signatures, chat with us, understand and motivate us. Beautiful and easy to use, products have to be fully customizable to match our personal preferences.Accomplishing these feats is easier said than done, but a solution has emerged in the form of Experience design (XD), the unifying approach to fusing business, technology and design around a user-centered philosophy.This book explores key dimensions of XD: Close collaboration among interdisciplinary teams, rapid iteration and ongoing user validation. We cover the processes, methodologies, tools, techniques and best-practices practitioners use throughout the entire product development life-cycle, as ideas are transformed to into positive experiences which lead to perpetual customer engagement and brand loyalty.