Develop modern user interfaces using Angular 6 and its component-based architecture. Key Features * Build better web applications with highly scalable concepts using Angular * Learn new ways to design your web applications * Build a fully functional web application that lets you tackle real-world user interface problems using Angular components Book Description Angular framework embraces a mature user interface (UI) component architecture, a powerful tool when developing scalable application interfaces. The simple and deterministic design of Angular components supports you in building large and scalable component-based applications. Mastering Angular Components covers a new holistic way of thinking about UI development, and helps you discover the power of Angular 6 components through various examples. The book starts with an introduction to component-based user interfaces and how Angular 6 manages this concept. Following a step-by-step approach, you will build a fully functional task-management application using Angular. You’ll start with basic layout components, adding some core task-management components before completing the first draft of your application. You will then move on to working through a refactoring exercise in order to learn how to enhance the way you deal with states and data. Once you have got to grips with all this, you will study how to make use of the Angular router within your application. By the end of this book, you will be able to constantly refine the functionality of your application and create components that render SVG graphics, add a time-tracking feature, visualize data using third-party library Chartist, and even create a plugin architecture using Angular components. What you will learn * Use TypeScript to create Angular 6 components * Leverage component composition to solve complex UI requirements * Build an architecture using pure components and container components * Explore the basics of RxJS observable streams and use them to build your application reactively * Communicate between components using child queries * Implement the Angular router to make your application navigable * Build reusable and dynamic graphical content using Angular components and SVG * Integrate third-party libraries such as Moment.js and Chartist into your existing Angular application Who this book is for Mastering Angular Components is for you if you are an Angular developer who already has a good understanding of basic frontend web technologies such as JavaScript, HTML, and CSS.

The essential blueprints and workflow you need to build successful AI business applications Key Features *Learn and master the essential blueprints to program AI for real-world business applications *Gain insights into how modern AI and machine learning solve core business challenges *Acquire practical techniques and a workflow that can build AI applications using state-of-the-art software libraries *Work with a practical, code-based strategy for creating successful AI solutions in your business Book Description AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You’ll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you’ll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You’ll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a ‘trending now’ section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers’ questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you’ll also learn how to prepare for future advances in AI. You’ll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. What you will learn *An essential toolbox of blueprints and advanced techniques for building AI business applications *How to design and deploy AI applications that meet today’s business needs *A workflow from first design stages to practical code solutions in your next AI projects *Solutions for AI projects that involve social media analytics and recommendation engines *Practical projects and techniques for sentiment analysis and helpful chatbots *A blueprint for AI projects that recommend products based on customer purchasing habits *How to prepare yourself for the next decade of AI and machine learning advancements Who this book is for Programming AI Business Applications provides an introduction to AI with real-world examples. This book can be read and understood by programmers and students without requiring previous AI experience. The projects in this book make use of Java and Python and several popular and state-of-the-art opensource AI libraries.

Get into the world of smart data security using machine learning algorithms and Python libraries Key Features *Learn machine learning algorithms and cybersecurity fundamentals *Automate your daily workflow by applying use cases to many facets of security *Implement smart machine learning solutions to detect various cybersecurity problems Book Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learn *Use machine learning algorithms with complex datasets to implement cybersecurity concepts *Implement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problems *Learn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDA *Understand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimes *Use TensorFlow in the cybersecurity domain and implement real-world examples *Learn how machine learning and Python can be used in complex cyber issues Who this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

Over 100 recipes to get up and running with the modern Linux administration ecosystem Key Features *Understand and implement the core system administration tasks in Linux *Discover tools and techniques to troubleshoot your Linux system *Maintain a healthy system with good security and backup practices Book Description Linux is one of the most widely used operating systems among system administrators,and even modern application and server development is heavily reliant on the Linux platform. The Linux Administration Cookbook is your go-to guide to get started on your Linux journey. It will help you understand what that strange little server is doing in the corner of your office, what the mysterious virtual machine languishing in Azure is crunching through, what that circuit-board-like thing is doing under your office TV, and why the LEDs on it are blinking rapidly. This book will get you started with administering Linux, giving you the knowledge and tools you need to troubleshoot day-to-day problems, ranging from a Raspberry Pi to a server in Azure, while giving you a good understanding of the fundamentals of how GNU/Linux works. Through the course of the book, you’ll install and configure a system, while the author regales you with errors and anecdotes from his vast experience as a data center hardware engineer, systems administrator, and DevOps consultant. By the end of the book, you will have gained practical knowledge of Linux, which will serve as a bedrock for learning Linux administration and aid you in your Linux journey. What you will learn *Install and manage a Linux server, both locally and in the cloud *Understand how to perform administration across all Linux distros *Work through evolving concepts such as IaaS versus PaaS, containers, and automation *Explore security and configuration best practices *Troubleshoot your system if something goes wrong *Discover and mitigate hardware issues, such as faulty memory and failing drives Who this book is for If you are a system engineer or system administrator with basic experience of working with Linux, this book is for you.

Leverage Elastic Stack’s machine learning features to gain valuable insight from your data Key Features * Combine machine learning with the analytic capabilities of Elastic Stack * Analyze large volumes of search data and gain actionable insight from them * Use external analytical tools with your Elastic Stack to improve its performance Book Description 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. What you will learn * Install the Elastic Stack to use machine learning features * Understand how Elastic machine learning is used to detect a variety of anomaly types * Apply effective anomaly detection to IT operations and security analytics * Leverage the output of Elastic machine learning in custom views, dashboards, and proactive alerting * Combine your created jobs to correlate anomalies of different layers of infrastructure * Learn various tips and tricks to get the most out of Elastic machine learning Who this book is for If you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key Features * Build state-of-the-art algorithms that can solve your business' problems * Learn how to find hidden patterns in your data * Revise key concepts with hands-on exercises using real-world datasets Book Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learn * Implement clustering methods such as k-means, agglomerative, and divisive * Write code in R to analyze market segmentation and consumer behavior * Estimate distribution and probabilities of different outcomes * Implement dimension reduction using principal component analysis * Apply anomaly detection methods to identify fraud * Design algorithms with R and learn how to edit or improve code Who this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.

Create powerful data visualizations and unlock intelligent business insights with Tableau Key Features * Explore all the latest Tableau 2019 features and redefine business analytics for your organization * Create impressive data visualizations and interactive dashboards to get insights from your data * Learn effective data storytelling to transform how your business leverages data and makes decisions Book Description Tableau is the gold standard of business intelligence and visual analytics tools in every industry. It enables rapid data visualization and interpretation with charts, graphs, dashboards, and much more. Updated with the latest features of Tableau, this book takes you from the foundations of the Tableau 2019 paradigm through to advanced topics. This third edition of the bestselling guide by Tableau Zen Master, Milligan, will help you come to grips with updated features, such as set actions and transparent views. Beginning with installation, you'll create your first visualizations with Tableau and then explore practical examples and advanced techniques. You'll create bar charts, tree maps, scatterplots, time series, and a variety of other visualizations. Next, you'll discover techniques to overcome challenges presented by data structure and quality and engage in effective data storytelling and decision making with business critical information. Finally, you'll be introduced to Tableau Prep, and learn how to use it to integrate and shape data for analysis. By the end of this book, you will be equipped to leverage the powerful features of Tableau 2019 for decision making. What you will learn * Develop stunning visualizations that explain complexity with clarity * Explore the exciting new features of Tableau Desktop and Tableau Prep * Connect to various data sources to bring all your data together * Uncover techniques to prep and structure your data for easy analysis * Create and use calculations to solve problems and enrich analytics * Master advanced topics such as sets, LOD calcs, and much more * Enable smart decisions with clustering, distribution, and forecasting * Share your data stories to build a culture of trust and action Who this book is for This Tableau book is for anyone who wants to understand data. If you’re new to Tableau, don’t worry. This book builds on the foundations to help you understand how Tableau really works and then builds on that knowledge with practical examples before moving on to advanced techniques. Working experience with databases will be useful but is not necessary to get the most out of this book.

Build cost-effective and robust cloud solutions with Google Cloud Platform (GCP) using these simple and practical recipes Key Features * Explore the various service offerings of the GCP * Host a Python application on Google Compute Engine * Securely maintain application states with Cloud Storage, Datastore, and Bigtable Book Description GCP is a cloud computing platform with a wide range of products and services that enable you to build and deploy cloud-hosted applications. This Learning Path will guide you in using GCP and designing, deploying, and managing applications on Google Cloud. You will get started by learning how to use App Engine to access Google's scalable hosting and build software that runs on this framework. With the help of Google Compute Engine, you’ll be able to host your workload on virtual machine instances. The later chapters will help you to explore ways to implement authentication and security, Cloud APIs, and command-line and deployment management. As you hone your skills, you’ll understand how to integrate your new applications with various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. Following this, the book will teach you how to streamline your workflow with tools, including Source Repositories, Container Builder, and Stackdriver. You'll also understand how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerts for your production systems. By the end of this Learning Path, you'll be well versed with GCP’s development tools and be able to develop, deploy, and manage highly scalable and reliable applications. This Learning Path includes content from the following Packt products: * Google Cloud Platform for Developers Ted Hunter and Steven Porter * Google Cloud Platform Cookbook by Legorie Rajan PS What you will learn * Host an application using Google Cloud Functions * Migrate a MySQL database to Cloud Spanner * Configure a network for a highly available application on GCP * Learn simple image processing using Storage and Cloud Functions * Automate security checks using Policy Scanner * Deploy and run services on App Engine and Container Engine * Minimize downtime and mitigate issues with Stackdriver Monitoring and Debugger * Integrate with big data solutions, including BigQuery, Dataflow, and Pub/Sub Who this book is for This Learning Path is for IT professionals, engineers, and developers who want to implement Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this Learning Path useful. Basic understanding of GCP and its services is a must.

Choose the smarter way to learn about containerizing your applications and running them in production. Key Features * Deploy and manage highly scalable, containerized applications with Kubernetes * Build high-availability Kubernetes clusters * Secure your applications via encapsulation, networks, and secrets Book Description Kubernetes is an open source orchestration platform for managing containers in a cluster environment. This Learning Path introduces you to the world of containerization, in addition to providing you with an overview of Docker fundamentals. As you progress, you will be able to understand how Kubernetes works with containers. Starting with creating Kubernetes clusters and running applications with proper authentication and authorization, you'll learn how to create high-availability Kubernetes clusters on Amazon Web Services (AWS), and also learn how to use kubeconfig to manage different clusters. Whether it is learning about Docker containers and Docker Compose, or building a continuous delivery pipeline for your application, this Learning Path will equip you with all the right tools and techniques to get started with containerization. By the end of this Learning Path, you will have gained hands-on experience of working with Docker containers and orchestrators, including SwarmKit and Kubernetes. This Learning Path includes content from the following Packt products: * Kubernetes Cookbook - Second Edition by Hideto Saito, Hui-Chuan Chloe Lee, and Ke-Jou Carol Hsu * Learn Docker - Fundamentals of Docker 18.x by Gabriel N. Schenker What you will learn * Build your own container cluster * Run a highly distributed application with Docker Swarm or Kubernetes * Update or rollback a distributed application with zero downtime * Containerize your traditional or microservice-based application * Build a continuous delivery pipeline for your application * Track metrics and logs for every container in your cluster * Implement container orchestration to streamline deploying and managing applications Who this book is for This beginner-level Learning Path is designed for system administrators, operations engineers, DevOps engineers, and developers who want to get started with Docker and Kubernetes. Although no prior experience with Docker is required, basic knowledge of Kubernetes and containers will be helpful.

Learn to distribute network traffic, optimize application delivery, and defend network-level threats. Key Features * Quickly get up and running with Azure networking solutions * Level-up your cloud networking skills by planning, implementing, configuring, and securing your infrastructure network with Azure * Leverage Azure networking services to provide applications highly available and fault tolerant environment Book Description Microsoft provides organizations with an effective way of managing their network with Azure's networking services. No matter the size of your organization, Azure provides a way to highly reliable performance and secure connectivity with its networking services. The book starts with an introduction to the Azure networking like creating Azure virtual networks, designing address spaces and subnets. Then you will learn to create and manage network security groups, application security groups, and IP addresses in Azure. Gradually, we move on to various aspects like S2S, P2S, and Vnet2Vnet connections, DNS and routing, load balancers and traffic manager. This book will cover every aspect and function required to deliver practical recipes to help readers learn from basic cloud networking practices to planning, implementing, and securing their infrastructure network with Azure. Readers will not only be able to upscale their current environment but will also learn to monitor, diagnose, and ensure secure connectivity. After learning to deliver a robust environment readers will also gain meaningful insights from recipes on best practices. By the end of this book, readers will gain hands-on experience in providing cost-effective solutions that benefit organizations. What you will learn * Learn to create Azure networking services * Understand how to create and work on hybrid connections * Configure and manage Azure network services * Learn ways to design high availability network solutions in Azure * Discover how to monitor and troubleshoot Azure network resources * Learn different methods of connecting local networks to Azure virtual networks Who this book is for This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on the Azure cloud. Some prior understanding of Microsoft Azure will be a plus point.

Use self-driven data centers to reduce management complexity by deploying Infrastructure as Code to gain value from investments. Key Features * Add smart capabilities in VMware Workspace ONE to deliver customer insights and improve overall security * Optimize your HPC and big data infrastructure with the help of machine learning * Automate your VMware data center operations with machine learning Book Description This book presents an introductory perspective on how machine learning plays an important role in a VMware environment. It offers a basic understanding of how to leverage machine learning primitives, along with a deeper look into integration with the VMware tools used for automation today. This book begins by highlighting how VMware addresses business issues related to its workforce, customers, and partners with emerging technologies such as machine learning to create new, intelligence-driven, end user experiences. You will learn how to apply machine learning techniques incorporated in VMware solutions for data center operations. You will go through management toolsets with a focus on machine learning techniques. At the end of the book, you will learn how the new vSphere Scale-Out edition can be used to ensure that HPC, big data performance, and other requirements can be met (either through development or by fine-tuning guidelines) with mainstream products. What you will learn * Orchestrate on-demand deployments based on defined policies * Automate away common problems and make life easier by reducing errors * Deliver services to end users rather than to virtual machines * Reduce rework in a multi-layered scalable manner in any cloud * Explore the centralized life cycle management of hybrid clouds * Use common code so you can run it across any cloud Who this book is for This book is intended for those planning, designing, and implementing the virtualization/cloud components of the Software-Defined Data Center foundational infrastructure. It helps users to put intelligence in their automation tasks to get self driving data center. It is assumed that the reader has knowledge of, and some familiarity with, virtualization concepts and related topics, including storage, security, and networking.

Build modern day application by implementing Material Design principles in React applications using Material-UI. Key Features * Grasp the needs React components for UI elements * Master the style and theme of the tools to go along with these components * Get to grips with all the React best practices to build a modern application Book Description Material-UI is a component library for rendering UI elements, using modern best practices from React and Material Design. This book will show you how you can create impressive and captivating modern day web apps by implementing Material Design considerations. The primary objective of this book is to help you use several Material-UI components to build larger UI functionality. We will also focus on React best practices in conjunction with Material-UI components – using state, context, and other new React 16.8 features properly. This book will start with layout and navigation and then dive into presenting the information with Material-UI components. It will then talk about the different components for user interactions. By the end of this book, you will know how to improve the look and feel of your applications using Material-UI components. What you will learn * Learn to build the overall structure and navigation for your Material-UI app * Learn to present simple and complex information in a variety of ways * Build interactive and intuitive controls * Design portable themes and styles for all of your Material-UI apps * Group content into sections using tabs and expansion panels * Learn how to design a general page layout with Material-UI grids * Use lists for complex data, and cards for detailed information Who this book is for They are JavaScript developers who have some basic knowledge of React and would want to implement Material Design principles in React applications using Material-UI. The reader wants to build a user interface using React components but doesn’t want to invent their own style or UX framework.

Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key Features * Study new techniques for marketing analytics * Explore uses of machine learning to power your marketing analyses * Work through each stage of data analytics with the help of multiple examples and exercises Book Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learn * Analyze and visualize data in Python using pandas and Matplotlib * Study clustering techniques, such as hierarchical and k-means clustering * Create customer segments based on manipulated data * Predict customer lifetime value using linear regression * Use classification algorithms to understand customer choice * Optimize classification algorithms to extract maximal information Who this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.

Enhance your programming skills to build exciting robotic projects Key Features * Build an intelligent robot that can detect and avoid obstacles and respond to voice commands * Detect and track objects and faces using OpenCV * Control your robot with a GUI button designed using Qt5 Book Description C++ is one of the most popular legacy programming languages for robotics, and a combination of C++ and robotics hardware is used in many leading industries. This book will bridge the gap between Raspberry Pi and C/C++ programming and enable you to develop applications for Raspberry Pi. To follow along with the projects covered in the book, you can implement C programs in Raspberry Pi with the wiringPi library. With this book, you’ll develop a fully functional car robot and write programs to move it in different directions. You’ll then create an obstacle - avoiding robot using an ultrasonic sensor. Furthermore, you’ll find out how to control the robot wirelessly using your PC/Mac. This book will also help you work with object detection and tracking using OpenCV, and guide you through exploring face detection techniques. Finally, you will create an Android app and control the robot wirelessly with an Android smartphone. By the end of this book, you will have gained experience in developing a robot using Raspberry Pi and C/C++ programming. What you will learn * Install software in Raspberry Pi compatible with C++ programming * Program the Raspberry Pi in C++ to run a motor * Control RPi-powered robot wirelessly with your laptop or PC * Program an RPi camera using OpenCV Control a Raspberry Pi robot with voice commands * Implement face and object detection with Raspberry Pi Who this book is for This book is for developers, programmers, and robotics enthusiasts interested in leveraging C++ to build exciting robotics applications. Prior knowledge of C++ is necessary to understand the projects covered in this book.

Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features * Learn and implement machine learning algorithms in a variety of real-life scenarios * Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques * Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn * Use predictive modeling and apply it to real-world problems * Explore data visualization techniques to interact with your data * Learn how to build a recommendation engine * Understand how to interact with text data and build models to analyze it * Work with speech data and recognize spoken words using Hidden Markov Models * Get well versed with reinforcement learning, automated ML, and transfer learning * Work with image data and build systems for image recognition and biometric face recognition * Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.

Get close and comfortable with Unity and build applications that run on HoloLens, Daydream, and Oculus Rift Key Features * Build fun augmented reality applications using ARKit, ARCore, and Vuforia * Explore virtual reality by developing more than 10 engaging projects * Learn how to integrate AR and VR concepts together in a single application Book Description Unity is the leading platform to develop mixed reality experiences because it provides a great pipeline for working with 3D assets. Using a practical and project-based approach, this Learning Path educates you about the specifics of AR and VR development using Unity 2018 and Unity 3D. You’ll learn to integrate, animate, and overlay 3D objects on your camera feed, before moving on to implement sensor-based AR applications. You’ll explore various concepts by creating an AR application using Vuforia for both macOS and Windows for Android and iOS devices. Next, you’ll learn how to develop VR applications that can be experienced with devices, such as Oculus and Vive. You’ll also explore various tools for VR development: gaze-based versus hand controller input, world space UI canvases, locomotion and teleportation, timeline animation, and multiplayer networking. You’ll learn the Unity 3D game engine via the interactive Unity Editor and C# programming. By the end of this Learning Path, you’ll be fully equipped to develop rich, interactive mixed reality experiences using Unity. This Learning Path includes content from the following Packt products: * Unity Virtual Reality Projects - Second Edition by Jonathan Linowes * Unity 2018 Augmented Reality Projects by Jesse Glover What you will learn * Create 3D scenes to learn about world space and scale * Move around your scenes using locomotion and teleportation * Create filters or overlays that work with facial recognition software * Interact with virtual objects using eye gaze, hand controllers, and user input events * Design and build a VR storytelling animation with a soundtrack and timelines * Create social VR experiences with Unity networking Who this book is for If you are a game developer familiar with 3D computer graphics and interested in building your own AR and VR games or applications, then this Learning Path is for you. Any prior experience in Unity and C# will be an advantage. In all, this course teaches you the tools and techniques to develop engaging mixed reality applications.

Take your neural networks to a whole new level with the simplicity and modularity of Keras, the most commonly used high-level neural networks API. Key Features * Solve complex machine learning problems with precision * Evaluate, tweak, and improve your deep learning models and solutions * Use different types of neural networks to solve real-world problems Book Description Though designing neural networks is a sought-after skill, it is not easy to master. With Keras, you can apply complex machine learning algorithms with minimum code. Applied Deep Learning with Keras starts by taking you through the basics of machine learning and Python all the way to gaining an in-depth understanding of applying Keras to develop efficient deep learning solutions. To help you grasp the difference between machine and deep learning, the book guides you on how to build a logistic regression model, first with scikit-learn and then with Keras. You will delve into Keras and its many models by creating prediction models for various real-world scenarios, such as disease prediction and customer churning. You’ll gain knowledge on how to evaluate, optimize, and improve your models to achieve maximum information. Next, you’ll learn to evaluate your model by cross-validating it using Keras Wrapper and scikit-learn. Following this, you’ll proceed to understand how to apply L1, L2, and dropout regularization techniques to improve the accuracy of your model. To help maintain accuracy, you’ll get to grips with applying techniques including null accuracy, precision, and AUC-ROC score techniques for fine tuning your model. By the end of this book, you will have the skills you need to use Keras when building high-level deep neural networks. What you will learn * Understand the difference between single-layer and multi-layer neural network models * Use Keras to build simple logistic regression models, deep neural networks, recurrent neural networks, and convolutional neural networks * Apply L1, L2, and dropout regularization to improve the accuracy of your model * Implement cross-validate using Keras wrappers with scikit-learn * Understand the limitations of model accuracy Who this book is for If you have basic knowledge of data science and machine learning and want to develop your skills and learn about artificial neural networks and deep learning, you will find this book useful. Prior experience of Python programming and experience with statistics and logistic regression will help you get the most out of this book. Although not necessary, some familiarity with the scikit-learn library will be an added bonus.

Understand Gang of Four, architectural, functional, and reactive design patterns and how to implement them on modern Java platforms, such as Java 12 and beyond Key Features * Learn OOP, functional, and reactive patterns for creating readable and maintainable code * Explore architectural patterns and practices for building scalable and reliable applications * Tackle all kinds of performance-related issues and streamline development using design patterns Book Description Java design patterns are reusable and proven solutions to software design problems. This book covers over 60 battle-tested design patterns used by developers to create functional, reusable, and flexible software. Hands-On Design Patterns with Java starts with an introduction to the Unified Modeling Language (UML), and delves into class and object diagrams with the help of detailed examples. You'll study concepts and approaches to object-oriented programming (OOP) and OOP design patterns to build robust applications. As you advance, you'll explore the categories of GOF design patterns, such as behavioral, creational, and structural, that help you improve code readability and enable large-scale reuse of software. You’ll also discover how to work effectively with microservices and serverless architectures by using cloud design patterns, each of which is thoroughly explained and accompanied by real-world programming solutions. By the end of the book, you’ll be able to speed up your software development process using the right design patterns, and you’ll be comfortable working on scalable and maintainable projects of any size. What you will learn * Understand the significance of design patterns for software engineering * Visualize software design with UML diagrams * Strengthen your understanding of OOP to create reusable software systems * Discover GOF design patterns to develop scalable applications * Examine programming challenges and the design patterns that solve them * Explore architectural patterns for microservices and cloud development Who this book is for If you are a developer who wants to learn how to write clear, concise, and effective code for building production-ready applications, this book is for you. Familiarity with the fundamentals of Java is assumed.

A definitive guide covering all the core concepts necessary to pass the Salesforce Administrator Certification exam Key Features * Understand critical design considerations for setting up Salesforce CRM * Facilitate and manage the transition from Salesforce Classic to Lightning Experience * Learn key functions of application security to manage user profiles and data Book Description Salesforce’s winter ’19 release offers a host of new features for CRM designed to meet your sales and marketing requirements. With this comprehensive guide to implementing Salesforce CRM, administrators of all levels can easily get a thorough understanding of the platform. This Salesforce handbook begins by guiding you in setting up users and security and then progresses to configuration, data management, and data analytics. You’ll discover process automation and approval mechanisms, while also exploring the functional areas of Sales Cloud, Service Cloud, Marketing Cloud, and Salesforce Chatter. This book covers Salesforce CRM system administration in a practical way, and it’ll serve as an invaluable reference for both new administrators and experienced professionals. Furthermore, you’ll also delve into Salesforce mobile apps and mobile administration, along with Salesforce Adoption Manager. You’ll gain insights into Lightning Experience, Salesforce's new app, and learn how its modern design and sleek interface helps you to build customizable components. Finally, we'll see how the two versions compare and help manage the transition from Salesforce Classic to Lightning Experience.?? By the end of the book, you will have mastered the techniques to configure and control various user interface features in Salesforce CRM. What you will learn * Configure a variety of user interface features in Salesforce CRM * Understand the capabilities of the Salesforce CRM sharing model * Explore Einstein Analytics - Salesforce's new wave of advanced reporting * Get to grips with the Lightning Process Builder workflow * Set up user profiles, security, and login access mechanisms * Find out how Apex and Visualforce coding can be used in Salesforce CRM * Manage the transition from Salesforce Classic to Lightning Experience * Implement data manipulation features to apply best practices in data management Who this book is for This book is for administrators who want to develop and strengthen their Salesforce CRM skills in the areas of configuration and system management. Whether you are a new or experienced professional, this book will enhance your knowledge and understanding of Salesforce CRM features.

Learn how to write automated tests for Dynamics 365 Business Central and see how to implement it in your daily work Key Features * Leverage automated testing to advance over traditional manual testing methods * Write, design, and implement automated tests * Explore various testing frameworks and tools compatible with Microsoft Dynamics 365 Business Central Book Description Dynamics 365 Business Central is the new cloud-based SaaS ERP proposition from Microsoft. It’s not as simple as it used to be way back when it was called Navigator, Navision Financials, or Microsoft Business Solutions-Navision. Our development practices are becoming more formal, and with this, the call for test automation is pressing on us. This book will teach you to leverage testing tools available with Dynamics 365 Business Central to perform automated testing. We’ll begin with a quick introduction to automated testing, followed by an overview of test automation in Dynamics 365 Business Central. Then you’ll learn to design and build automated tests and we’ll go through some efficient methods to get from requirements to application and testing code. Lastly, you’ll learn to incorporate your own and Microsoft tests into your daily development practice. By the end of the book, you’ll be able to write your own automated tests for Dynamics 365 Business Central. What you will learn * Understand what automated tests are, and when and why to use them * Explore the five pillars of the Testability Framework of Business Central * Design and write automated tests for Business Central * Make use of standard automated tests and their helper libraries * Integrate automated tests into your development practice Who this book is for This book is for consultants, testers, developers, and development managers working with Microsoft Dynamics NAV and Business Central. Being a book on automated testing techniques, it also caters to both functional and technical development teams.

Explore the fundamentals of Dynamics 365 Business Central and the Visual Studio Code development environment with the help of useful examples and case studies Key Features * Tailor your applications to best suit the needs of your business * Explore the latest features of Business Central with examples curated by industry experts * Integrate Business Central features in your applications with this comprehensive guide Book Description Microsoft Dynamics 365 Business Central is a full ERP business solution suite with a robust set of development tools to support customization and enhancement. These tools can be used to tailor Business Central's in-built applications to support complete management functions for finance, supply chain, manufacturing, and operations. Using a case study approach, this book will introduce you to Dynamics 365 Business Central and Visual Studio Code development tools to help you become a productive Business Central developer. You'll also learn how to evaluate a product's development capabilities and manage Business Central-based development and implementation. You'll explore application structure, the construction of and uses for each object type, and how it all fits together to build apps that meet special business requirements. By the end of this book, you'll understand how to design and develop high-quality software using the Visual Studio Code development environment, the AL language paired with the improved editor, patterns, and features. What you will learn * Programming using the AL language in the Visual Studio Code development environment * Explore functional design and development using AL * How to build interactive pages and learn how to extract data for users * How to use best practices to design and develop modifications for new functionality integrated with the standard Business Central software * Become familiar with deploying the broad range of components available in a Business Central system * Create robust, viable systems to address specific business requirements Who this book is for If you want to learn about Dynamics 365 Business Central's powerful and extensive built-in development capabilities, this is the book for you. ERP consultants and managers of Business Central development will also find this book helpful. Although you aren't expected to have worked with Dynamics Business Central, basic understanding of programming and familiarity with business application software will help you understand the concepts covered in this book.