Explore and understand data with the powerful data visualization techniques of Tableau, and then communicate insights in powerful ways Key Features *Apply best practices in data visualization and chart types exploration *Explore the latest version of Tableau Desktop with hands-on examples *Understand the fundamentals of Tableau storytelling Book Description Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You’ll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. This Learning Path includes content from the following Packt products: *Learning Tableau 10 - Second Edition by N. Milligan *Getting Started with Tableau 2018.x by Tristan Guillevin What you will learn *Build effective visualizations, dashboards, and story points *Build basic to more advanced charts with step-by-step recipes *Become familiar row-level, aggregate, and table calculations *Dig deep into data with clustering and distribution models *Prepare and transform data for analysis *Leverage Tableau’s mapping capabilities to visualize data *Use data storytelling techniques to aid decision making strategy Who this book is for Tableau 10 Complete Reference is designed for anyone who wants to understand their data better and represent it in an effective manner. It is also used for BI professionals and data analysts who want to do better at their jobs.

Step-by-step guide to build high performing predictive applications Key Features *Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects *Explore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanations *Learn to deploy a predictive model's results as an interactive application Book Description Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming. What you will learn *Get to grips with the main concepts and principles of predictive analytics *Learn about the stages involved in producing complete predictive analytics solutions *Understand how to define a problem, propose a solution, and prepare a dataset *Use visualizations to explore relationships and gain insights into the dataset *Learn to build regression and classification models using scikit-learn *Use Keras to build powerful neural network models that produce accurate predictions *Learn to serve a model's predictions as a web application Who this book is for This book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this exciting field will greatly benefit from reading this book. All you need is to be proficient in Python programming and have a basic understanding of statistics and college-level algebra.

A comprehensive guide to Android forensics, from setting up the workstation to analyzing key artifacts Key Features *Get up and running with modern mobile forensic strategies and techniques *Analyze the most popular Android applications using free and open source forensic tools *Learn malware detection and analysis techniques to investigate mobile cybersecurity incidents Book Description Many forensic examiners rely on commercial, push-button tools to retrieve and analyze data, even though there is no tool that does either of these jobs perfectly. Learning Android Forensics will introduce you to the most up-to-date Android platform and its architecture, and provide a high-level overview of what Android forensics entails. You will understand how data is stored on Android devices and how to set up a digital forensic examination environment. As you make your way through the chapters, you will work through various physical and logical techniques to extract data from devices in order to obtain forensic evidence. You will also learn how to recover deleted data and forensically analyze application data with the help of various open source and commercial tools. In the concluding chapters, you will explore malware analysis so that you’ll be able to investigate cybersecurity incidents involving Android malware. By the end of this book, you will have a complete understanding of the Android forensic process, you will have explored open source and commercial forensic tools, and will have basic skills of Android malware identification and analysis. What you will learn *Understand Android OS and architecture *Set up a forensics environment for Android analysis *Perform logical and physical data extractions *Learn to recover deleted data *Explore how to analyze application data *Identify malware on Android devices *Analyze Android malware Who this book is for If you are a forensic analyst or an information security professional wanting to develop your knowledge of Android forensics, then this is the book for you. Some basic knowledge of the Android mobile platform is expected.

Demonstrate fundamentals of Deep Learning and neural network methodologies using Keras 2.x Key Features *Experimental projects showcasing the implementation of high-performance deep learning models with Keras. * *Use-cases across reinforcement learning, natural language processing, GANs and computer vision. * *Build strong fundamentals of Keras in the area of deep learning and artificial intelligence. Book Description Keras 2.x Projects explains how to leverage the power of Keras to build and train state-of-the-art deep learning models through a series of practical projects that look at a range of real-world application areas. To begin with, you will quickly set up a deep learning environment by installing the Keras library. Through each of the projects, you will explore and learn the advanced concepts of deep learning and will learn how to compute and run your deep learning models using the advanced offerings of Keras. You will train fully-connected multilayer networks, convolutional neural networks, recurrent neural networks, autoencoders and generative adversarial networks using real-world training datasets. The projects you will undertake are all based on real-world scenarios of all complexity levels, covering topics such as language recognition, stock volatility, energy consumption prediction, faster object classification for self-driving vehicles, and more. By the end of this book, you will be well versed with deep learning and its implementation with Keras. You will have all the knowledge you need to train your own deep learning models to solve different kinds of problems. What you will learn *Apply regression methods to your data and understand how the regression algorithm works *Understand the basic concepts of classification methods and how to implement them in the Keras environment *Import and organize data for neural network classification analysis *Learn about the role of rectified linear units in the Keras network architecture *Implement a recurrent neural network to classify the sentiment of sentences from movie reviews *Set the embedding layer and the tensor sizes of a network Who this book is for If you are a data scientist, machine learning engineer, deep learning practitioner or an AI engineer who wants to build speedy intelligent applications with minimal lines of codes, then this book is the best fit for you. Sound knowledge of machine learning and basic familiarity with Keras library would be useful.

Leverage the power of machine learning on mobiles and build intelligent mobile applications with ease Key Features *Build smart mobile applications for Android and iOS devices *Use popular machine learning toolkits such as Core ML and TensorFlow Lite *Explore cloud services for machine learning that can be used in mobile apps Book Description Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples. You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains. By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices. What you will learn *Build intelligent machine learning models that run on Android and iOS *Use machine learning toolkits such as Core ML, TensorFlow Lite, and more *Learn how to use Google Mobile Vision in your mobile apps *Build a spam message detection system using Linear SVM *Using Core ML to implement a regression model for iOS devices *Build image classification systems using TensorFlow Lite and Core ML Who this book is for If you are a mobile app developer or a machine learning enthusiast keen to use machine learning to build smart mobile applications, this book is for you. Some experience with mobile application development is all you need to get started with this book. Prior experience with machine learning will be an added bonus

Learn the foundations of blockchain technology - its core concepts and algorithmic solutions across cryptography, peer-to-peer technology, and game theory. Key Features * Learn the core concepts and foundations of the blockchain and cryptocurrencies * Understand the protocols and algorithms behind decentralized applications * Master how to architect, build, and optimize blockchain applications Book Description Blockchain technology is a combination of three popular concepts: cryptography, peer-to-peer networking, and game theory. This book is for anyone who wants to dive into blockchain from first principles and learn how decentralized applications and cryptocurrencies really work. This book begins with an overview of blockchain technology, including key definitions, its purposes and characteristics, so you can assess the full potential of blockchain. All essential aspects of cryptography are then presented, as the backbone of blockchain. For readers who want to study the underlying algorithms of blockchain, you’ll see Python implementations throughout. You’ll then learn how blockchain architecture can create decentralized applications. You’ll see how blockchain achieves decentralization through peer-to-peer networking, and how a simple blockchain can be built in a P2P network. You’ll learn how these elements can implement a cryptocurrency such as Bitcoin, and the wider applications of blockchain work through smart contracts. Blockchain optimization techniques, and blockchain security strategies are then presented. To complete this foundation, we consider blockchain applications in the financial and non-financial sectors, and also analyze the future of blockchain. A study of blockchain use cases includes supply chains, payment systems, crowdfunding, and DAOs, which rounds out your foundation in blockchain technology. What you will learn * The core concepts and technical foundations of blockchain * The algorithmic principles and solutions that make up blockchain and cryptocurrencies * Blockchain cryptography explained in detail * How to realize blockchain projects with hands-on Python code * How to architect the blockchain and blockchain applications * Decentralized application development with MultiChain, NEO, and Ethereum * Optimizing and enhancing blockchain performance and security * Classical blockchain use cases and how to implement them Who this book is for This book is for anyone who wants to dive into blockchain technology from first principles and build a foundational knowledge of blockchain. Familiarity with Python will be helpful if you want to follow how the blockchain protocols are implemented. For readers who are blockchain application developers, most of the applications used in this book can be executed on any platform.

An effective guide to becoming an AWS Certified SysOps Administrator Key Features * Not only pass the certification with confidence but also enhance your skills to solving real-world scenarios. * A practical guide to getting you hands-on experience with application management, deployment, operation. * Enhance your AWS skills with practice questions and mock tests. Book Description AWS certifications are becoming one of the must have certifications for any IT professional working on an AWS Cloud platform. This book will act as your one stop preparation guide to validate your technical expertise in deployment, management, and operations on the AWS platform. Along with exam specific content this book will also deep dive into real world scenarios and hands-on instructions. This book will revolve around concepts like teaching you to deploy, manage, and operate scalable, highly available, and fault tolerant systems on AWS. You will also learn to migrate an existing on-premises application to AWS. You get hands-on experience in selecting the appropriate AWS service based on compute, data, or security requirements. This book will also get you well versed with estimating AWS usage costs and identifying operational cost control mechanisms. By the end of this book, you will be all prepared to implement and manage resources efficiently on the AWS cloud along with confidently passing the AWS Certified SysOps Administrator – Associate exam. What you will learn * Create and manage users, groups, and permissions using AWS IAM services * Create a secure VPC with public and private subnets, Network Access Control, and security groups * Get started with launching your first EC2 instance, and working with it * Handle application traffic with ELB and monitor AWS resources with CloudWatch * Work with S3, Glacier, and CloudFront * Work across distributed application components using SWF * Understand event-based processing with Lambda and messaging SQS and SNS in AWS * Get familiar with AWS deployment concepts and tools including Elastic Beanstalk, CloudFormation and AWS OpsWorks Who this book is for If you are a system administrator or a system engineer interested in leveraging the AWS platform to deploy applications then, this book is for you. IT professionals interested in passing the AWS Certified Sysops Administrator will also benefit from this book. Some basic understanding of working AWS components would do wonders.

Get to grips with the unified, highly scalable distributed storage system and learn how to design and implement it. Key Features * Explore Ceph's architecture in detail * Implement a Ceph cluster successfully and gain deep insights into its best practices * Leverage the advanced features of Ceph, including erasure coding, tiering, and BlueStore Book Description This Learning Path takes you through the basics of Ceph all the way to gaining in-depth understanding of its advanced features. You’ll gather skills to plan, deploy, and manage your Ceph cluster. After an introduction to the Ceph architecture and its core projects, you’ll be able to set up a Ceph cluster and learn how to monitor its health, improve its performance, and troubleshoot any issues. By following the step-by-step approach of this Learning Path, you’ll learn how Ceph integrates with OpenStack, Glance, Manila, Swift, and Cinder. With knowledge of federated architecture and CephFS, you’ll use Calamari and VSM to monitor the Ceph environment. In the upcoming chapters, you’ll study the key areas of Ceph, including BlueStore, erasure coding, and cache tiering. More specifically, you’ll discover what they can do for your storage system. In the concluding chapters, you will develop applications that use Librados and distributed computations with shared object classes, and see how Ceph and its supporting infrastructure can be optimized. By the end of this Learning Path, you'll have the practical knowledge of operating Ceph in a production environment. This Learning Path includes content from the following Packt products: * Ceph Cookbook by Michael Hackett, Vikhyat Umrao and Karan Singh * Mastering Ceph by Nick Fisk * Learning Ceph, Second Edition by Anthony D'Atri, Vaibhav Bhembre and Karan Singh What you will learn * Understand the benefits of using Ceph as a storage solution * Combine Ceph with OpenStack, Cinder, Glance, and Nova components * Set up a test cluster with Ansible and virtual machine with VirtualBox * Develop solutions with Librados and shared object classes * Configure BlueStore and see its interaction with other configurations * Tune, monitor, and recover storage systems effectively * Build an erasure-coded pool by selecting intelligent parameters Who this book is for If you are a developer, system administrator, storage professional, or cloud engineer who wants to understand how to deploy a Ceph cluster, this Learning Path is ideal for you. It will help you discover ways in which Ceph features can solve your data storage problems. Basic knowledge of storage systems and GNU/Linux will be beneficial.

Leverage the power of Kubernetes to build an efficient software delivery pipeline. Key Features * Learn about DevOps, containers, and Kubernetes all within one handy book * A practical guide to container management and orchestration * Learn how to monitor, log, and troubleshoot your Kubernetes applications Book Description Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure. What you will learn * Learn fundamental and advanced DevOps skills and tools * Get a comprehensive understanding of containers * Dockerize an application * Administrate and manage Kubernetes cluster * Extend the cluster functionality with custom resources * Understand Kubernetes network and service mesh * Implement Kubernetes logging and monitoring * Manage Kubernetes services in Amazon Web Services, Google Cloud Platform,and Microsoft Azure Who this book is for This book is for anyone who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills are required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced, you can get a deeper understanding of all the tools and technique described in the book.

Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features * Build independent machine learning (ML) systems leveraging the best features of R 3.5 * Understand and apply different machine learning techniques using real-world examples * Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn * Prepare data for machine learning methods with ease * Understand how to write production-ready code and package it for use * Produce simple and effective data visualizations for improved insights * Master advanced methods, such as Boosted Trees and deep neural networks * Use natural language processing to extract insights in relation to text * Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.

Build, secure, and deploy real-world serverless applications in AWS and peek into the serverless cloud offerings from Azure, Google Cloud, and IBM Cloud Key Features * Build serverless applications with AWS Lambda, AWS CloudFormation and AWS CloudWatch * Perform data analytics and natural language processing(NLP)on the AWS serverless platform * Explore various design patterns and best practices involved in serverless computing Book Description Managing physical servers will be a thing of the past once you’re able to harness the power of serverless computing. If you’re already prepped with the basics of serverless computing, Serverless Programming Cookbook will help you take the next step ahead. This recipe-based guide provides solutions to problems you might face while building serverless applications. You'll begin by setting up Amazon Web Services (AWS), the primary cloud provider used for most recipes. The next set of recipes will cover various components to build a Serverless application including REST APIs, database, user management, authentication, web hosting, domain registration, DNS management, CDN, messaging, notifications and monitoring. The book also introduces you to the latest technology trends such as Data Streams, Machine Learning and NLP. You will also see patterns and practices for using various services in a real world application. Finally, to broaden your understanding of Serverless computing, you'll also cover getting started guides for other cloud providers such as Azure, Google Cloud Platform and IBM cloud. By the end of this book, you’ll have acquired the skills you need to build serverless applications efficiently using various cloud offerings. What you will learn * Serverless computing in AWS and explore services with other clouds * Develop full-stack apps with API Gateway, Cognito, Lambda and DynamoDB * Web hosting with S3, CloudFront, Route 53 and AWS Certificate Manager * SQS and SNS for effective communication between microservices * Monitoring and troubleshooting with CloudWatch logs and metrics * Explore Kinesis Streams, Amazon ML models and Alexa Skills Kit Who this book is for For developers looking for practical solutions to common problems while building a serverless application, this book provides helpful recipes. To get started with this intermediate-level book, knowledge of basic programming is a must.

Explore the exciting world of machine learning with the fastest growing technology in the world Key Features * Understand various machine learning concepts with real-world examples * Implement a supervised machine learning pipeline from data ingestion to validation * Gain insights into how you can use machine learning in everyday life Book Description Machine learning—the ability of a machine to give right answers based on input data—has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support. With the help of fun examples, you'll gain experience working on the Python machine learning toolkit—from performing basic data cleaning and processing to working with a range of regression and classification algorithms. Once you’ve grasped the basics, you'll learn how to build and train your own models using advanced techniques such as decision trees, ensemble modeling, validation, and error metrics. You'll also learn data visualization techniques using powerful Python libraries such as Matplotlib and Seaborn. This book also covers ensemble modeling and random forest classifiers along with other methods for combining results from multiple models, and concludes by delving into cross-validation to test your algorithm and check how well the model works on unseen data. By the end of this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own! What you will learn * Understand the concept of supervised learning and its applications * Implement common supervised learning algorithms using machine learning Python libraries * Validate models using the k-fold technique * Build your models with decision trees to get results effortlessly * Use ensemble modeling techniques to improve the performance of your model * Apply a variety of metrics to compare machine learning models Who this book is for Applied Supervised Learning with Python is for you if you want to gain a solid understanding of machine learning using Python. It'll help if you to have some experience in any functional or object-oriented language and a basic understanding of Python libraries and expressions, such as arrays and dictionaries.

Explore Qt framework and APIs for building cross-platform applications for mobile devices, embedded systems, and IoT Key Features * Build cross-platform applications and deploy them across mobile and connected devices * Design 2D and 3D UIs for embedded systems using Yocto and Qt Creator * Build machine to machine automation solution using QtSensors, QtMQTT, and QtWebSockets Book Description Qt is a world-class framework, helping you to develop rich graphical user interfaces (GUIs) and multi-platform applications that run on all major desktop platforms and most mobile or embedded platforms. The framework helps you connect the dots across platforms and between online and physical experience. This book will help you leverage the fully-featured Qt framework and its modular cross-platform library classes and intuitive APIs to develop applications for mobile, IoT, and industrial embedded systems. Considerations such as screen size, device orientation changes, and small memory will be discussed. We will focus on various core aspects of embedded and mobile systems, such as connectivity, networking, and sensors; there is no IoT without sensors. You will learn how to quickly design a flexible, fast, and responsive UI that looks great. Going further, you will implement different elements in a matter of minutes and synchronize the UI elements with the 3D assets with high precision. You will learn how to create high-performance embedded systems with 3D/2D user interfaces, and deploy and test on your target hardware. The book will explore several new features, including Qt for WebAssembly. At the end of this book, you will learn about creating a full software stack for embedded Linux systems using Yocto and Boot to Qt for Device Creation. What you will learn * Explore the latest features of Qt, such as preview for Qt for Python and Qt for WebAssembly * Create fluid UIs with a dynamic layout for different sized screens * Deploy embedded applications on Linux systems using Yocto * Design Qt APIs for building applications for embedded and mobile devices * Utilize connectivity for networked and machine automated applications * Discover effective techniques to apply graphical effects using Qt Quick apps Who this book is for The book is ideal for mobile developers, embedded systems engineers and enthusiasts who are interested in building cross-platform applications with Qt. Prior knowledge of C++ is required.

Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features * Study ROS, the main development framework for robotics, in detail * Learn all about convolutional neural networks, recurrent neural networks, and robotics * Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn * Explore the ROS and build a basic robotic system * Understand the architecture of neural networks * Identify conversation intents with NLP techniques * Learn and use the embedding with Word2Vec and GloVe * Build a basic CNN and improve it using generative models * Use deep learning to implement artificial intelligence(AI)and object recognition * Develop a simple object recognition system using CNNs * Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.

Work with the powerful subscription software, Office 365 to increase your organization's efficiency by managing file sharing, email exchange and much more. Key Features * Become well versed with Office 365 and leverage its capabilities for your business * Speed up your workflow and effectively collaborate using Office Web Apps * Learn to set audio and web conferences and seamlessly access your workspace Book Description Microsoft Office 365 combines the popular Office suite with next-generation cloud computing capabilities. With this user guide, you'll be able to implement its software features for effective business communication and collaboration. This book begins by providing you with a quick introduction to the user interface (UI) and the most commonly used features of Office 365. After covering the core aspects of this suite, you'll learn how to perform various email functions via Exchange. Next, you will learn how to communicate using Skype for Business and Microsoft Teams. To boost your productivity, this book will help you learn everything from using instant messaging to conducting audio and web conferences, and even accessing business information from any location. In the final chapters, you will learn to work in a systematic style using file management and collaboration with OneDrive for Business using SharePoint. By the end of this book, you'll be equipped with the knowledge you need to take full advantage of Office 365 and level up your organization's productivity. What you will learn * Understand the UI of Office 365 * Perform a variety of email functions through Exchange * Communicate using Skype for Business and Microsoft Teams * Explore file management using OneDrive for Business * Collaborate using SharePoint * Understand how to leverage Office 365 in your daily tasks Who this book is for If you are an IT professional who wants to upgrade your traditional Office suite, this book is for you. Users looking to learn, configure, manage, and maintain an Office 365 environment in their organization will also find this book useful. Some understanding of Microsoft Office Suite and cloud computing basics will be beneficial.

Solve complex business problems by understanding users better, finding the right problem to solve, and building lean event-driven systems to give your customers what they really want Key Features * Apply DDD principles using modern tools such as EventStorming, Event Sourcing, and CQRS * Learn how DDD applies directly to various architectural styles such as REST, reactive systems, and microservices * Empower teams to work flexibly with improved services and decoupled interactions Book Description Developers across the world are rapidly adopting DDD principles to deliver powerful results when writing software that deals with complex business requirements. This book will guide you in involving business stakeholders when choosing the software you are planning to build for them. By figuring out the temporal nature of behavior-driven domain models, you will be able to build leaner, more agile, and modular systems. You’ll begin by uncovering domain complexity and learn how to capture the behavioral aspects of the domain language. You will then learn about EventStorming and advance to creating a new project in .NET Core 2.1; you’ll also and write some code to transfer your events from sticky notes to C#. The book will show you how to use aggregates to handle commands and produce events. As you progress, you’ll get to grips with Bounded Contexts, Context Map, Event Sourcing, and CQRS. After translating domain models into executable C# code, you will create a frontend for your application using Vue.js. In addition to this, you’ll learn how to refactor your code and cover event versioning and migration essentials. By the end of this DDD book, you will have gained the confidence to implement the DDD approach in your organization and be able to explore new techniques that complement what you’ve learned from the book. What you will learn * Discover and resolve domain complexity together with business stakeholders * Avoid common pitfalls when creating the domain model * Study the concept of Bounded Context and aggregate * Design and build temporal models based on behavior and not only data * Explore benefits and drawbacks of Event Sourcing * Get acquainted with CQRS and to-the-point read models with projections * Practice building one-way flow UI with Vue.js * Understand how a task-based UI conforms to DDD principles Who this book is for This book is for .NET developers who have an intermediate level understanding of C#, and for those who seek to deliver value, not just write code. Intermediate level of competence in JavaScript will be helpful to follow the UI chapters.

Implement Business Central and explore methods to upgrade to NAV 2018 Key Features *Learn the key roles of Dynamics NAV partner and the roles within your customer's organization *Create configuration packages and perform data migration *Explore Microsoft Dynamics 365 Business Central to use Dynamics NAV 2018 functionalities in the Cloud Book Description Microsoft Dynamics Business Central is a full business solution suite and a complete ERP solution, which contains a robust set of development tools; these tools can help you to gain control over your business and can simplify supply chains, manufacturing, and operations. Implementing Microsoft Dynamics 365 Business Central On-Premise covers the latest features of Dynamics Business Central and NAV from the end users' and developers' perspectives. It also provides an insight into different tools available for implementation, whether it's a new installation or migrating from the previous version of Dynamics NAV. This book will take you from an introduction to Dynamics NAV 2018 through to exploring all the techniques related to implementation and migration. You will also learn to expand functionalities within your existing Microsoft Dynamics NAV installation, perform data analysis, and implement free third-party add-ons to your existing installation. As you progress through the book, you will learn to work with third-party add-on tools. In the concluding chapters, you will explore Dynamics 365 Business Central, the new Cloud solution based on the Microsoft NAV platform, and techniques for using Docker and Sandbox to develop applications. By the end of the book, you will have gained a deep understanding of the key components for successful Dynamics NAV implementation for an organization. What you will learn *Explore new features introduced in Microsoft Dynamics NAV 2018 *Migrate to Microsoft Dynamics NAV 2018 from previous versions *Learn abstract techniques for data analysis, reporting, and debugging *Install, configure, and use additional tools for business intelligence, document management, and reporting *Discover Dynamics 365 Business Central and several other Microsoft services *Utilize different tools to develop applications for Business Central Who this book is for Implementing Microsoft Dynamics 365 Business Central On-Premise is for Dynamics NAV partners and end users who want to know everything about Dynamics NAV implementation. This book is for you if you want to be a project manager or get involved with Dynamics NAV, but do not have the expertise to write code yourself. This book can also help you to understand the need to move to Business Central and its advantages.

A definitive guide on frontend development with Angular from design to deployment Key Features *Develop web applications from scratch using Angular and TypeScript *Explore reactive programming principles and RxJS to develop and test apps easily *Study continuous integration and deployment on the AWS cloud Book Description If you have been burnt by unreliable JavaScript frameworks before, you will be amazed by the maturity of the Angular platform. Angular enables you to build fast, efficient, and real-world web apps. In this Learning Path, you'll learn Angular and to deliver high-quality and production-grade Angular apps from design to deployment. You will begin by creating a simple fitness app, using the building blocks of Angular, and make your final app, Personal Trainer, by morphing the workout app into a full-fledged personal workout builder and runner with an advanced directive building - the most fundamental and powerful feature of Angular. You will learn the different ways of architecting Angular applications using RxJS, and some of the patterns that are involved in it. Later you’ll be introduced to the router-first architecture, a seven-step approach to designing and developing mid-to-large line-of-business apps, along with popular recipes. By the end of this book, you will be familiar with the scope of web development using Angular, Swagger, and Docker, learning patterns and practices to be successful as an individual developer on the web or as a team in the Enterprise. This Learning Path includes content from the following Packt products: *Angular 6 by Example by Chandermani Arora, Kevin Hennessy *Architecting Angular Applications with Redux, RxJS, and NgRx by Christoffer Noring *Angular 6 for Enterprise-Ready Web Applications by Doguhan Uluca What you will learn *Develop web applications from scratch using Angular and TypeScript *Explore reactive programming principles, RxJS to develop and test apps efficiently *Study continuous integration and deployment your Angular app on the AWS cloud Who this book is for If you're a JavaScript or frontend developer looking to gain comprehensive experience of using Angular for end-to-end enterprise-ready applications, this Learning Path is for you.

Over 60 recipes to achieve a robust and advanced backup and recovery solution leveraging SCDPM Key Features *Adapt to the modern data center design challenges and improve storage efficiency *Effective recipes to help you create your own robust architectural designs *Solve data protection and recovery problems in your organization Book Description System Center Data Protection Manager (SCDPM) is a robust enterprise backup and recovery system that contributes to your BCDR strategy by facilitating the backup and recovery of enterprise data. With an increase in data recovery and protection problems faced in organizations, it has become important to keep data safe and recoverable. This book contains recipes that will help you upgrade to SCDPM and it covers the advanced features and functionality of SCDPM. This book starts by helping you install SCDPM and then moves on to post-installation and management tasks. You will come across a lot of useful recipes that will help you recover your VMware and Hyper-V VMs. It will also walk you through tips for monitoring SCDPM in different scenarios. Next, the book will also offer insights into protecting windows workloads followed by best practices on SCDPM. You will also learn to back up your Azure Stack Infrastructure using Azure Backup. You will also learn about recovering data from backup and implementing disaster recovery. Finally, the book will show you how to configure the protection groups to enable online protection and troubleshoot Microsoft Azure Backup Agent. What you will learn *Install and prepare SQL Server for the SCDPM database *Reduce backup storage with SCDPM and data deduplication *Learn about the prerequisites for supported Hyper-V Server protection *Integrate SCDPM with other System Center products to build optimal services *Protect and restore the SCDPM database *Protect your data center by integrating SCDPM with Azure Backup *Manually create online recovery points and recover production data from Azure *Protect and learn about the requirements to recover Azure Stack with SCDPM Who this book is for If you are an SCDPM administrator, this book will help you verify your knowledge and provide you with everything you need to know about the new release of System Center Data Protection Manager.

A concise walk-through of CentOS 7, starting from installation to securing it’s environment. Key Features *No previous Linux environment experience needed for reading this book *Get comfortable with a popular and stable Red Hat Enterprise Linux distribution *Most of the command line based concepts are explained with graphics Book Description Linux kernel development has been the worlds largest collaborative project to date. With this practical guide, you will learn Linux through one of its most popular and stable distributions. This book will introduce you to essential Linux skills using CentOS 7. It describes how a Linux system is organized, and will introduce you to key command-line concepts you can practice on your own. It will guide you in performing basic system administration tasks and day-to-day operations in a Linux environment. You will learn core system administration skills for managing a system running CentOS 7 or a similar operating system, such as RHEL 7, Scientific Linux, and Oracle Linux. You will be able to perform installation, establish network connectivity and user and process management, modify file permissions, manage text files using the command line, and implement basic security administration after covering this book. By the end of this book, you will have a solid understanding of working with Linux using the command line. What you will learn *Understand file system hierarchy and essential command-line skills *Use Vi editor, I/O redirections and how to work with common text manipulating tools *Create, delete, modify user accounts and manage passwords and their aging policy *Manage file ownership, permissions, and ACL *Execute process management and monitoring on the command line *Validate and manage network configuration using nmcli *Manage remote logins using SSH and file transfer using SCP and Rsync *Understand system logging, how to control system services with systemd and systemctl, and manage firewalId Who this book is for Any individual who wants to learn how to use Linux as server or desktop in his environment. Whether you are a developer, budding system administrator, or tech lover with no previous Linux administration background, you will be able to start your journey in Linux using CentOS 7 with this book.

Explore the best tools and techniques to create lightweight, maintainable, and scalable Python web services Key Features *Combine Python with different data sources to build complex RESTful APIs from scratch *Configure and fine-tune your APIs using the best tools and techniques available *Use command-line and GUI tools to test CRUD operations performed by RESTful Web Services or APIs Book Description Python is the language of choice for millions of developers worldwide that builds great web services in RESTful architecture. This second edition of Hands-On RESTful Python Web Services will cover the best tools you can use to build engaging web services. This book shows you how to develop RESTful APIs using the most popular Python frameworks and all the necessary stacks with Python, combined with related libraries and tools. You’ll learn to incorporate all new features of Python 3.7, Flask 1.0.2, Django 2.1, Tornado 5.1, and also a new framework, Pyramid. As you advance through the chapters, you will get to grips with each of these frameworks to build various web services, and be shown use cases and best practices covering when to use a particular framework. You’ll then successfully develop RESTful APIs with all frameworks and understand how each framework processes HTTP requests and routes URLs. You’ll also discover best practices for validation, serialization, and deserialization. In the concluding chapters, you will take advantage of specific features available in certain frameworks such as integrated ORMs, built-in authorization and authentication, and work with asynchronous code. At the end of each framework, you will write tests for RESTful APIs and improve code coverage. By the end of the book, you will have gained a deep understanding of the stacks needed to build RESTful web services. What you will learn *Select the most appropriate framework based on requirements *Develop complex RESTful APIs from scratch using Python *Use requests handlers, URL patterns, serialization, and validations *Add authentication, authorization, and interaction with ORMs and databases *Debug, test, and improve RESTful APIs with four frameworks *Design RESTful APIs with frameworks and create automated tests Who this book is for This book is for web developers who have a working knowledge of Python and would like to build amazing web services by taking advantage of the various frameworks of Python. You should have some knowledge of RESTful APIs.