- Table View
- List View
Hands-On Artificial Intelligence for Beginners: An introduction to AI concepts, algorithms, and their implementation
by Patrick D. SmithGrasp the fundamentals of Artificial Intelligence and build your own intelligent systems with easeKey FeaturesEnter the world of AI with the help of solid concepts and real-world use casesExplore AI components to build real-world automated intelligenceBecome well versed with machine learning and deep learning conceptsBook DescriptionVirtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world.Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games.By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications.What you will learnUse TensorFlow packages to create AI systemsBuild feedforward, convolutional, and recurrent neural networksImplement generative models for text generationBuild reinforcement learning algorithms to play gamesAssemble RNNs, CNNs, and decoders to create an intelligent assistantUtilize RNNs to predict stock market behaviorCreate and scale training pipelines and deployment architectures for AI systemsWho this book is forThis book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.
Modern JavaScript Web Development Cookbook: Easy solutions to common and everyday JavaScript development problems
by Ruben Oliva Ramos Federico KerekiThis book is for you if you want to explore the latest JavaScript features, frameworks, and tools to build complete web applications, including server- and client-side code. A basic working knowledge of JavaScript would be beneficial, as you will be introduced to the latest version of ES8 (2017).
Hands-On Security in DevOps: Ensure continuous security, deployment, and delivery with DevSecOps
by Tony HsuProtect your organization's security at all levels by introducing the latest strategies for securing DevOpsKey FeaturesIntegrate security at each layer of the DevOps pipelineDiscover security practices to protect your cloud services by detecting fraud and intrusionExplore solutions to infrastructure security using DevOps principlesBook DescriptionDevOps has provided speed and quality benefits with continuous development and deployment methods, but it does not guarantee the security of an entire organization. Hands-On Security in DevOps shows you how to adopt DevOps techniques to continuously improve your organization’s security at every level, rather than just focusing on protecting your infrastructure.This guide combines DevOps and security to help you to protect cloud services, and teaches you how to use techniques to integrate security directly in your product. You will learn how to implement security at every layer, such as for the web application, cloud infrastructure, communication, and the delivery pipeline layers. With the help of practical examples, you’ll explore the core security aspects, such as blocking attacks, fraud detection, cloud forensics, and incident response. In the concluding chapters, you will cover topics on extending DevOps security, such as risk assessment, threat modeling, and continuous security.By the end of this book, you will be well-versed in implementing security in all layers of your organization and be confident in monitoring and blocking attacks throughout your cloud services.What you will learnUnderstand DevSecOps culture and organizationLearn security requirements, management, and metricsSecure your architecture design by looking at threat modeling, coding tools and practicesHandle most common security issues and explore black and white-box testing tools and practicesWork with security monitoring toolkits and online fraud detection rulesExplore GDPR and PII handling case studies to understand the DevSecOps lifecycleWho this book is forHands-On Security in DevOps is for system administrators, security consultants, and DevOps engineers who want to secure their entire organization. Basic understanding of Cloud computing, automation frameworks, and programming is necessary.
Hands-On Artificial Intelligence with TensorFlow: Useful techniques in machine learning and deep learning for building intelligent applications
by Amir Ziai Ankit DixitExploit TensorFlow's capabilities to build artificial intelligence applicationsKey FeaturesExploit TensorFlow's new features to power your artificial intelligence appsImplement machine learning, deep learning, and reinforcement learning models with TensorflowBuild intelligent applications for computer vision, NLP, and healthcare, among othersBook DescriptionArtificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more.Hands-On Artificial Intelligence with TensorFlow gives you a rundown of essential AI concepts and their implementation with TensorFlow, also highlighting different approaches to solving AI problems using machine learning and deep learning techniques. In addition to this, the book covers advanced concepts, such as reinforcement learning, generative adversarial networks (GANs), and multimodal learning.Once you have grasped all this, you’ll move on to exploring GPU computing and neuromorphic computing, along with the latest trends in quantum computing. You’ll work through case studies that will help you examine AI applications in the important areas of computer vision, healthcare, and FinTech, and analyze their datasets. In the concluding chapters, you’ll briefly investigate possible developments in AI that we can expect to see in the future.By the end of this book, you will be well-versed with the essential concepts of AI and their implementation using TensorFlow.What you will learnExplore the core concepts of AI and its different approachesUse the TensorFlow framework for smart applicationsImplement various machine and deep learning algorithms with TensorFlowDesign self-learning RL systems and implement generative modelsPerform GPU computing efficiently using best practicesBuild enterprise-grade apps for computer vision, NLP, and healthcareWho this book is forHands-On Artificial Intelligence with TensorFlow is for you if you are a machine learning developer, data scientist, AI researcher, or anyone who wants to build artificial intelligence applications using TensorFlow. You need to have some working knowledge of machine learning to get the most out of this book.
Hands-On Chatbot Development with Alexa Skills and Amazon Lex: Create custom conversational and voice interfaces for your Amazon Echo devices and web platforms
by Sam WilliamsBuild artificial intelligence (AI) powered voice and text conversational interfaces with AmazonKey FeaturesDevelop Alexa Skills to create a working voice user interface (VUI)Integrate Amazon Lex chatbots into Facebook, Slack, and text messagesLearn to use AWS Lambda, Alexa Skills Kit, and Amazon LexBook DescriptionHave you ever wondered how Alexa apps are made, how voice-enabled technologies work, or how chatbots function? And why tech giants such as Amazon and Google are investing in voice technologies? A better question is: why should I start developing on these platforms? Hands-On Chatbot Development with Alexa Skills and Amazon Lex covers all features of the Alexa Skills kit with real-world examples that help you develop skills to integrate Echo and chatbots into Facebook, Slack, and Twilio with the Amazon Lex platform.The book starts with teaching you how to set up your local environment and AWS CLI so that you can automate the process of uploading AWS Lambda from your local machine. You will then learn to develop Alexa Skills and Lex chatbots using Lambda functions to control functionality. Once you’ve come to grips with this, you will learn to create increasingly complex chatbots, integrate Amazon S3, and change the way Alexa talks to the user. In the concluding chapters, we shift our focus to Amazon Lex and messaging chatbots. We will explore Alexa, learn about DynamoDB databases, and add cards to user conversations.By the end of this book, you will have explored a full set of technologies that will enable you to create your own voice and messaging chatbots using Amazon.What you will learnCreate a development environment using Alexa Skills Kit, AWS CLI, and Node.jsBuild Alexa Skills and Lex chatbots from scratchGain access to third-party APIs from your Alexa Skills and Lex chatbotsUse AWS services such as Amazon S3 and DynamoDB to enhance the abilities of your Alexa Skills and Amazon Lex chatbotsPublish a Lex chatbot to Facebook Messenger, Twilio SMS, and SlackCreate a custom website for your Lex chatbotsDevelop your own skills for Alexa-enabled devices such as the EchoWho this book is forHands-On Chatbot Development with Alexa Skills and Amazon Lex is for developers who are interested in building conversational bots and Alexa skills with Amazon. Prior experience with JavaScript programming is required.
Hands-On Recommendation Systems with Python: Start building powerful and personalized, recommendation engines with Python
by Rounak BanikWith Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the webKey FeaturesBuild industry-standard recommender systemsOnly familiarity with Python is requiredNo need to wade through complicated machine learning theory to use this bookBook DescriptionRecommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible..In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.What you will learnGet to grips with the different kinds of recommender systemsMaster data-wrangling techniques using the pandas libraryBuilding an IMDB Top 250 CloneBuild a content based engine to recommend movies based on movie metadataEmploy data-mining techniques used in building recommendersBuild industry-standard collaborative filters using powerful algorithmsBuilding Hybrid Recommenders that incorporate content based and collaborative flteringWho this book is forIf you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.
R Web Scraping Quick Start Guide: Techniques and tools to crawl and scrape data from websites
by Olgun AydinWeb Scraping techniques are getting more popular, since data is as valuable as oil in 21st century. Through this book get some key knowledge about using XPath, regEX; web scraping libraries for R like rvest and RSelenium technologies. Key FeaturesTechniques, tools and frameworks for web scraping with RScrape data effortlessly from a variety of websites Learn how to selectively choose the data to scrape, and build your datasetBook DescriptionWeb scraping is a technique to extract data from websites. It simulates the behavior of a website user to turn the website itself into a web service to retrieve or introduce new data. This book gives you all you need to get started with scraping web pages using R programming.You will learn about the rules of RegEx and Xpath, key components for scraping website data. We will show you web scraping techniques, methodologies, and frameworks. With this book's guidance, you will become comfortable with the tools to write and test RegEx and XPath rules. We will focus on examples of dynamic websites for scraping data and how to implement the techniques learned. You will learn how to collect URLs and then create XPath rules for your first web scraping script using rvest library. From the data you collect, you will be able to calculate the statistics and create R plots to visualize them. Finally, you will discover how to use Selenium drivers with R for more sophisticated scraping. You will create AWS instances and use R to connect a PostgreSQL database hosted on AWS. By the end of the book, you will be sufficiently confident to create end-to-end web scraping systems using R.What you will learnWrite and create regEX rulesWrite XPath rules to query your dataLearn how web scraping methods workUse rvest to crawl web pagesStore data retrieved from the webLearn the key uses of Rselenium to scrape dataWho this book is forThis book is for R programmers who want to get started quickly with web scraping, as well as data analysts who want to learn scraping using R. Basic knowledge of R is all you need to get started with this book.
Hands-On Enterprise Automation with Python: Automate common administrative and security tasks with Python
by Bassem AlyInvent your own Python scripts to automate your infrastructureKey FeaturesMake the most of Python libraries and modules to automate your infrastructureLeverage Python programming to automate server configurations and administration tasksEfficiently develop your Python skill setBook DescriptionHands-On Enterprise Automation with Python starts by covering the set up of a Python environment to perform automation tasks, as well as the modules, libraries, and tools you will be using. We’ll explore examples of network automation tasks using simple Python programs and Ansible. Next, we will walk you through automating administration tasks with Python Fabric, where you will learn to perform server configuration and administration, along with system administration tasks such as user management, database management, and process management. As you progress through this book, you’ll automate several testing services with Python scripts and perform automation tasks on virtual machines and cloud infrastructure with Python. In the concluding chapters, you will cover Python-based offensive security tools and learn how to automate your security tasks.By the end of this book, you will have mastered the skills of automating several system administration tasks with Python.What you will learnUnderstand common automation modules used in PythonDevelop Python scripts to manage network devicesAutomate common Linux administration tasks with Ansible and FabricManaging Linux processesAdministrate VMware, OpenStack, and AWS instances with PythonSecurity automation and sharing code on GitHubWho this book is forHands-On Enterprise Automation with Python is for system administrators and DevOps engineers who are looking for an alternative to major automation frameworks such as Puppet and Chef. Basic programming knowledge with Python and Linux shell scripting is necessary.
Python: Gain practical insights by exploiting data in your business to build advanced predictive modeling applications
by Joseph J Ashish KumarKey Features A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Book Description Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling. Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books: 1. Learning Predictive Analytics with Python 2. Mastering Predictive Analytics with Python What you will learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis
Natural Language Processing with Java: Techniques for building machine learning and neural network models for NLP, 2nd Edition
by Richard M. Reese AshishSingh BhatiaExplore various approaches to organize and extract useful text from unstructured data using JavaKey FeaturesUse deep learning and NLP techniques in Java to discover hidden insights in textWork with popular Java libraries such as CoreNLP, OpenNLP, and MalletExplore machine translation, identifying parts of speech, and topic modelingBook DescriptionNatural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes.You’ll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you’ll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You’ll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more.By the end of this book, you’ll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications.What you will learnUnderstand basic NLP tasks and how they relate to one anotherDiscover and use the available tokenization enginesApply search techniques to find people, as well as things, within a documentConstruct solutions to identify parts of speech within sentencesUse parsers to extract relationships between elements of a documentIdentify topics in a set of documentsExplore topic modeling from a documentWho this book is forNatural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.
Mastering Machine Learning for Penetration Testing: Develop an extensive skill set to break self-learning systems using Python
by Chiheb ChebbiBecome a master at penetration testing using machine learning with PythonKey Features Identify ambiguities and breach intelligent security systems Perform unique cyber attacks to breach robust systems Learn to leverage machine learning algorithmsBook DescriptionCyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system.By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system.What you will learnTake an in-depth look at machine learningGet to know natural language processing (NLP)Understand malware feature engineeringBuild generative adversarial networks using Python librariesWork on threat hunting with machine learning and the ELK stackExplore the best practices for machine learningWho this book is forThis book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary.
Hands-On Full Stack Development with Spring Boot 2.0 and React: Build modern and scalable full stack applications using the Java-based Spring Framework 5.0 and React
by Juha HinkulaDevelop efficient and modern full-stack applications using Spring Boot and React 16Key Features Develop resourceful backends using Spring Boot and faultless frontends using React. Explore the techniques involved in creating a full-stack app by going through a methodical approach. Learn to add CRUD functionalities and use Material UI in the user interface to make it more user-friendly.Book DescriptionApart from knowing how to write frontend and backend code, a full-stack engineer has to tackle all the problems that are encountered in the application development life cycle, starting from a simple idea to UI design, the technical design, and all the way to implementing, testing, production, deployment, and monitoring. This book covers the full set of technologies that you need to know to become a full-stack web developer with Spring Boot for the backend and React for the frontend. This comprehensive guide demonstrates how to build a modern full-stack application in practice. This book will teach you how to build RESTful API endpoints and work with the data access Layer of Spring, using Hibernate as the ORM. As we move ahead, you will be introduced to the other components of Spring, such as Spring Security, which will teach you how to secure the backend. Then, we will move on to the frontend, where you will be introduced to React, a modern JavaScript library for building fast and reliable user interfaces, and its app development environment and components.You will also create a Docker container for your application. Finally, the book will lay out the best practices that underpin professional full-stack web development.What you will learn Create a RESTful web service with Spring Boot Understand how to use React for frontend programming Gain knowledge of how to create unit tests using JUnit Discover the techniques that go into securing the backend using Spring Security Learn how to use Material UI in the user interface to make it more user-friendly Create a React app by using the Create React App starter kit made by FacebookWho this book is forJava developers who are familiar with Spring, but have not yet built full-stack applications
Python Reinforcement Learning Projects: Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow
by Sean Saito Yang Wenzhuo Rajalingappaa ShanmugamaniDeploy autonomous agents in business systems using powerful Python libraries and sophisticated reinforcement learning modelsKey FeaturesImplement Q-learning and Markov models with Python and OpenAIExplore the power of TensorFlow to build self-learning modelsEight AI projects to gain confidence in building self-trained applicationsBook DescriptionReinforcement learning (RL) is the next big leap in the artificial intelligence domain, given that it is unsupervised, optimized, and fast. Python Reinforcement Learning Projects takes you through various aspects and methodologies of reinforcement learning, with the help of insightful projects.You will learn about core concepts of reinforcement learning, such as Q-learning, Markov models, the Monte-Carlo process, and deep reinforcement learning. As you make your way through the book, you’ll work on projects with various datasets, including numerical, text, video, and audio, and will gain experience in gaming, image rocessing, audio processing, and recommendation system projects. You’ll explore TensorFlow and OpenAI Gym to implement a deep learning RL agent that can play an Atari game. In addition to this, you will learn how to tune and configure RL algorithms and parameters by building agents for different kinds of games. In the concluding chapters, you’ll get to grips with building self-learning models that will not only uncover layers of data but also reason and make decisions.By the end of this book, you will have created eight real-world projects that explore reinforcement learning and will have handson experience with real data and artificial intelligence (AI) problems.What you will learnTrain and evaluate neural networks built using TensorFlow for RLUse RL algorithms in Python and TensorFlow to solve CartPole balancingCreate deep reinforcement learning algorithms to play Atari gamesDeploy RL algorithms using OpenAI UniverseDevelop an agent to chat with humans Implement basic actor-critic algorithms for continuous controlApply advanced deep RL algorithms to games such as MinecraftAutogenerate an image classifier using RLWho this book is forPython Reinforcement Learning Projects is for data analysts, data scientists, and machine learning professionals, who have working knowledge of machine learning techniques and are looking to build better performing, automated, and optimized deep learning models. Individuals who want to work on self-learning model projects will also find this book useful.
Mastering pfSense,: Manage, secure, and monitor your on-premise and cloud network with pfSense 2.4, 2nd Edition
by David ZientaraInstall and configure a pfSense router/firewall, and become a pfSense expert in the process.Key FeaturesYou can always do more to secure your software – so extend and customize your pfSense firewallBuild a high availability security system that’s fault-tolerant – and capable of blocking potential threatsPut the principles of better security into practice by implementing examples provided in the textBook DescriptionpfSense has the same reliability and stability as even the most popular commercial firewall offerings on the market – but, like the very best open-source software, it doesn’t limit you. You’re in control – you can exploit and customize pfSense around your security needs.Mastering pfSense - Second Edition, covers features that have long been part of pfSense such as captive portal, VLANs, traffic shaping, VPNs, load balancing, Common Address Redundancy Protocol (CARP), multi-WAN, and routing. It also covers features that have been added with the release of 2.4, such as support for ZFS partitions and OpenVPN 2.4. This book takes into account the fact that, in order to support increased cryptographic loads, pfSense version 2.5 will require a CPU that supports AES-NI. The second edition of this book places more of an emphasis on the practical side of utilizing pfSense than the previous edition, and, as a result, more examples are provided which show in step-by-step fashion how to implement many features.What you will learnConfigure pfSense services such as DHCP, Dynamic DNS, captive portal, DNS, NTP and SNMPSet up a managed switch to work with VLANsUse pfSense to allow, block and deny traffic, and to implement Network Address Translation (NAT)Make use of the traffic shaper to lower and raise the priority of certain types of trafficSet up and connect to a VPN tunnel with pfSenseIncorporate redundancy and high availability by utilizing load balancing and the Common Address Redundancy Protocol (CARP)Explore diagnostic tools in pfSense to solve network problemsWho this book is forThis book is for those with at least an intermediate understanding of networking. Prior knowledge of pfSense would be helpful but is not required.Those who have the resources to set up a pfSense firewall, either in a real or virtual environment, will especially benefit, as they will be able to follow along with the examples in the book.
Architecting Microsoft Azure Solutions – Exam Guide 70-535: A complete guide to passing the 70-535 Architecting Microsoft Azure Solutions exam
by Sjoukje ZaalGet certified as an Azure architect by acing the 70-535 Architecting Microsoft Solutions (70-535) exam using this comprehensive guide with full coverage of the exam objectivesKey FeaturesLearn to successfully design and architect powerful solutions on the Azure Cloud platformEnhance your skills with mock tests and practice questionsA detailed certification guide that will help you ace the 70-535 exam with confidenceBook DescriptionArchitecting Microsoft Azure Solutions: Exam Guide 70-535 will get Azure architects and developers up-to-date with the latest updates on Azure from an architecture and design perspective. The book includes all the topics that are still relevant from the previous 70-534 exam, and is updated with latest topics covered, including Artificial Intelligence, IoT, and architecture styles.This exam guide is divided into six parts, where the first part will give you a good understanding of how to design a compute infrastructure. It also dives into designing networking and data implementations. You will learn about designing solutions for Platform Service and operations. Next, you will be able to secure your resources and data, as well as design a mechanism for governance and policies. You will also understand the objective of designing solutions for Platform Services, by covering Artificial Intelligence, IoT, media services, and messaging solution concepts. Finally, you will cover the designing for operations objective. This objective covers application and platform monitoring, as well as designing alerting strategies and operations automation strategies. By the end of the book, you’ll have met all of the exam objectives, and will have all the information you need to ace the 70-535 exam. You will also have become an expert in designing solutions on Microsoft Azure.What you will learnUse Azure Virtual Machines to design effective VM deploymentsImplement architecture styles, like serverless computing and microservicesSecure your data using different security features and design effective security strategiesDesign Azure storage solutions using various storage featuresCreate identity management solutions for your applications and resourcesArchitect state-of-the-art solutions using Artificial Intelligence, IoT, and Azure Media ServicesUse different automation solutions that are incorporated in the Azure platformWho this book is forThis book is for architects and experienced developers, who are gearing up for the 70-535 exam. Technical architects interested in learning more about designing Cloud solutions will also find this book useful.
Hands-On Deep Learning with R: A practical guide to designing, building, and improving neural network models using R
by Michael Pawlus Rodger DevineExplore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and Deepnet Key Features Understand deep learning algorithms and architectures using R and determine which algorithm is best suited for a specific problem Improve models using parameter tuning, feature engineering, and ensembling Apply advanced neural network models such as deep autoencoders and generative adversarial networks (GANs) across different domains Book Description Deep learning enables efficient and accurate learning from a massive amount of data. This book will help you overcome a number of challenges using various deep learning algorithms and architectures with R programming. This book starts with a brief overview of machine learning and deep learning and how to build your first neural network. You'll understand the architecture of various deep learning algorithms and their applicable fields, learn how to build deep learning models, optimize hyperparameters, and evaluate model performance. Various deep learning applications in image processing, natural language processing (NLP), recommendation systems, and predictive analytics will also be covered. Later chapters will show you how to tackle recognition problems such as image recognition and signal detection, programmatically summarize documents, conduct topic modeling, and forecast stock market prices. Toward the end of the book, you will learn the common applications of GANs and how to build a face generation model using them. Finally, you'll get to grips with using reinforcement learning and deep reinforcement learning to solve various real-world problems. By the end of this deep learning book, you will be able to build and deploy your own deep learning applications using appropriate frameworks and algorithms. What you will learn Design a feedforward neural network to see how the activation function computes an output Create an image recognition model using convolutional neural networks (CNNs) Prepare data, decide hidden layers and neurons and train your model with the backpropagation algorithm Apply text cleaning techniques to remove uninformative text using NLP Build, train, and evaluate a GAN model for face generation Understand the concept and implementation of reinforcement learning in R Who this book is for This book is for data scientists, machine learning engineers, and deep learning developers who are familiar with machine learning and are looking to enhance their knowledge of deep learning using practical examples. Anyone interested in increasing the efficiency of their machine learning applications and exploring various options in R will also find this book useful. Basic knowledge of machine learning techniques and working knowledge of the R programming language is expected.
Mastering Dynamics 365 - Second Edition: An advanced guide to developing and customizing CRM solutions to improve your business applications, 2nd Edition
by Deepesh SomaniThis book is for those with Dynamics CRM knowledge who want to utilize the latest features available with Dynamics 365. It is also for skilled developers who are looking to move to the Microsoft stack to build business solution software. Extensive Dynamics CRM development experience would be beneficial.
Mastering Qt 5: Create stunning cross-platform applications using C++ with Qt Widgets and QML with Qt Quick, 2nd Edition
by Guillaume Lazar Robin PeneaAn In-depth guide updated with the latest version of Qt 5.11 including new features such as Quick Controls and Qt GamepadKey FeaturesUnleash the power of Qt 5.11 with C++Build applications using Qt Widgets (C++) or Qt Quick (QML)Create cross-platform applications for mobile and desktop platforms with Qt 5Book DescriptionQt 5.11 is an app development framework that provides a great user experience and develops full capability applications with Qt Widgets, QML, and even Qt 3D. Whether you're building GUI prototypes or fully-fledged cross-platform GUI applications with a native look and feel, Mastering Qt 5 is your fastest, easiest, and most powerful solution. This book addresses various challenges and teaches you to successfully develop cross-platform applications using the Qt framework, with the help of well-organized projects.Working through this book, you will gain a better understanding of the Qt framework, as well as the tools required to resolve serious issues, such as linking, debugging, and multithreading. You'll start off your journey by discovering the new Qt 5.11 features, soon followed by exploring different platforms and learning to tame them. In addition to this, you'll interact with a gamepad using Qt Gamepad. Each chapter is a logical step for you to complete in order to master Qt.By the end of this book, you'll have created an application that has been tested and is ready to be shipped.What you will learnCreate stunning UIs with Qt Widgets and Qt Quick 2Develop powerful, cross-platform applications with the Qt frameworkDesign GUIs with the Qt Designer and build a library in it for UI previewsHandle user interaction with the Qt signal or slot mechanism in C++Prepare a cross-platform project to host a third-party libraryUse the Qt Animation framework to display stunning effectsDeploy mobile apps with Qt and embedded platformsInteract with a gamepad using Qt GamepadWho this book is forMastering Qt 5 is for developers and programmers who want to build GUI-based applications. C++ knowledge is necessary, and knowing QT basics will help you get the most out of this book.
Hands-On Networking with Azure: Build large-scale, real-world apps using Azure networking solutions
by Mohamed WalyA step-by-step guide to get you up and running with Azure Networking Services and help you build solutions that leverage effective design patternsKey FeaturesLearn best practices for designing and implementing Azure Networking for Azure VMsFigure out the hidden secrets to designing a cost-effective environmentPlan, design, and implement various connectivity scenarios in AzureBook DescriptionMicrosoft Azure networking is one of themost valuable and important offeringsin Azure. No matter what solution youare building for the cloud, you'll find acompelling use for it. This book will getyou up to speed quickly on MicrosoftAzure Networking by teaching you howto use different networking services.By reading this book, you will develop astrong networking foundation for Azurevirtual machines and for expanding youron-premise environment to Azure.Hands-On Networking with Azure startswith an introduction to Microsoft Azurenetworking and creating Azure VirtualNetworks with subnets of different typeswithin them. The book helps you understandthe architecture of Azure networks. Youwill then learn the best practices fordesigning both Windows- and Linux-basedAzure VM networks. You will also learnto expand your networks into Azure andhow to use Azure DNS. Moreover, youwill master best practices for dealing withAzure Load Balancer and the solutions theyoffer in different scenarios. Finally, we willdemonstrate how the Azure ApplicationGateway works, offering various layer-7load balancing capabilities for applications.By the end of this book, you will be ableto architect your networking solutionsfor Azure.What you will learn Understand Azure networking anduse the right networking service tofulfill your needs Design Azure Networks forAzure VMs according tobest practices Span your environment with Azurenetworking solutions Learn to use Azure DNS Implement Azure Load Balancer forhighly available environments Distribute user traffic acrossthe world via the AzureTraffic Manager Control your application delivery withAzure Application GatewayWho this book is forThis book is for developers, IT professionals, and database admins who have prior experience of working on Microsoft Azure and want to make the most out of Azure Networking Services.
The Modern C++ Challenge: Become an expert programmer by solving real-world problems
by Marius BancilaTest your C++ programming skills by solving real-world programming problems covered in the bookKey Features Solve a variety of real-world programming and logic problems by leveraging the power of C++17 Test your skills in using language features, algorithms, data structures, design patterns, and more Explore areas such as cryptography, communication, and image handling in C++Book DescriptionC++ is one of the most widely-used programming languages and has applications in a variety of fields, such as gaming, GUI programming, and operating systems, to name a few. Through the years, C++ has evolved into (and remains) one of the top choices for software developers worldwide. This book will show you some notable C++ features and how to implement them to meet your application needs. Each problem is unique and doesn't just test your knowledge of the language; it tests your ability to think out of the box and come up with the best solutions. With varying levels of difficulty, you'll be faced with a wide variety of challenges. And in case you're stumped, you don't have to worry: we've got the best solutions to the problems in the book. So are you up for the challenge?What you will learn Serialize and deserialize JSON and XML data Perform encryption and signing to facilitate secure communication between parties Embed and use SQLite databases in your applications Use threads and asynchronous functions to implement generic purpose parallel algorithms Compress and decompress files to/from a ZIP archive Implement data structures such as circular buffer and priority queue Implement general purpose algorithms as well as algorithms that solve specific problems Create client-server applications that communicate over TCP/IP Consume HTTP REST services Use design patterns to solve real-world problemsWho this book is forThis book will appeal to C++ developers of all levels. There's a challenge inside for everyone.
Natural Language Processing with Python Quick Start Guide: Going from a Python developer to an effective Natural Language Processing Engineer
by Nirant KasliwalBuild and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learningKey FeaturesA no-math, code-driven programmer’s guide to text processing and NLPGet state of the art results with modern tooling across linguistics, text vectors and machine learningFundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorchBook DescriptionNLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a workflow for building NLP applications.We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn.We conclude by deploying these models as REST APIs with Flask.By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges.What you will learnUnderstand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpusWork with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clusteringDeep Learning in NLP using PyTorch with a code-driven introduction to PyTorchUsing an NLP project management Framework for estimating timelines and organizing your project into stagesHack and build a simple chatbot application in 30 minutesDeploy an NLP or machine learning application using Flask as RESTFUL APIsWho this book is forProgrammers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory.
Mastering Metasploit,: Take your penetration testing and IT security skills to a whole new level with the secrets of Metasploit, 3rd Edition
by Nipun JaswalDiscover the next level of network defense with the Metasploit frameworkKey FeaturesGain the skills to carry out penetration testing in complex and highly-secured environmentsBecome a master using the Metasploit framework, develop exploits, and generate modules for a variety of real-world scenariosGet this completely updated edition with new useful methods and techniques to make your network robust and resilientBook DescriptionWe start by reminding you about the basic functionalities of Metasploit and its use in the most traditional ways. You’ll get to know about the basics of programming Metasploit modules as a refresher and then dive into carrying out exploitation as well building and porting exploits of various kinds in Metasploit.In the next section, you’ll develop the ability to perform testing on various services such as databases, Cloud environment, IoT, mobile, tablets, and similar more services. After this training, we jump into real-world sophisticated scenarios where performing penetration tests are a challenge. With real-life case studies, we take you on a journey through client-side attacks using Metasploit and various scripts built on the Metasploit framework.By the end of the book, you will be trained specifically on time-saving techniques using Metasploit.What you will learnDevelop advanced and sophisticated auxiliary modulesPort exploits from PERL, Python, and many more programming languagesTest services such as databases, SCADA, and many moreAttack the client side with highly advanced techniquesTest mobile and tablet devices with MetasploitBypass modern protections such as an AntiVirus and IDS with MetasploitSimulate attacks on web servers and systems with Armitage GUIScript attacks in Armitage using CORTANA scriptingWho this book is forThis book is a hands-on guide to penetration testing using Metasploit and covers its complete development. It shows a number of techniques and methodologies that will help you master the Metasploit framework and explore approaches to carrying out advanced penetration testing in highly secured environments.
Redash v5 Quick Start Guide: Create and share interactive dashboards using Redash
by Alexander Leibzon Yael LeibzonLearn how to quickly generate business intelligence, insights and create interactive dashboards for digital storytelling through various data sources with RedashKey FeaturesLearn the best use of visualizations to build powerful interactive dashboardsCreate and share visualizations and data in your organizationWork with different complexities of data from different data sourcesBook DescriptionData exploration and visualization is vital to Business Intelligence, the backbone of almost every enterprise or organization. Redash is a querying and visualization tool developed to simplify how marketing and business development departments are exposed to data. If you want to learn to create interactive dashboards with Redash, explore different visualizations, and share the insights with your peers, then this is the ideal book for you.The book starts with essential Business Intelligence concepts that are at the heart of data visualizations. You will learn how to find your way round Redash and its rich array of data visualization options for building interactive dashboards. You will learn how to create data storytelling and share these with peers. You will see how to connect to different data sources to process complex data, and then visualize this data to reveal valuable insights. By the end of this book, you will be confident with the Redash dashboarding tool to provide insight and communicate data storytelling.What you will learnInstall Redash and troubleshoot installation errorsManage user roles and permissionsFetch data from various data sourcesVisualize and present data with RedashCreate active alerts based on your dataUnderstand Redash administration and customizationExport, share and recount stories with Redash visualizationsInteract programmatically with Redash through the Redash APIWho this book is forThis book is intended for Data Analysts, BI professionals and Data Developers, but can be useful to anyone who has a basic knowledge of SQL and a creative mind. Familiarity with basic BI concepts will be helpful, but no knowledge of Redash is required.
Blockchain Quick Reference: A guide to exploring decentralized blockchain application development
by Samanyu Chopra Brenn Hill Paul ValencourtUnderstand the Blockchain revolution and get to grips with Ethereum, Hyperledger Fabric, and Corda.Key FeaturesResolve common challenges and problems faced in the Blockchain domainStudy architecture, concepts, terminologies, and DappsMake smart choices using Blockchain for personal and business investmentsBook DescriptionBlockchain Quick Reference takes you through the electrifying world of blockchain technology and is designed for those who want to polish their existing knowledge regarding the various pillars of the blockchain ecosystem.This book is your go-to guide, teaching you how to apply principles and ideas for making your life and business better. You will cover the architecture, Initial Coin Offerings (ICOs), tokens, smart contracts, and terminologies of the blockchain technology, before studying how they work. All you need is a curious mind to get started with blockchain technology. Once you have grasped the basics, you will explore components of Ethereum, such as ether tokens, transactions, and smart contracts, in order to build simple Dapps. You will then move on to learning why Solidity is used specifically for Ethereum-based projects, followed by exploring different types of blockchain with easy-to-follow examples. All this will help you tackle challenges and problems. By the end of this book, you will not only have solved current and future problems relating to blockchain technology but will also be able to build efficient decentralized applications.What you will learnUnderstand how blockchain architecture components workAcquaint yourself with cryptography and the mechanics behind blockchainApply consensus protocol to determine the business sustainabilityUnderstand what ICOs and crypto-mining are and how they workCreate cryptocurrency wallets and coins for transaction mechanismsUnderstand the use of Ethereum for smart contract and DApp developmentWho this book is forBlockchain Quick Reference is for you if you are a developer who wants to get well-versed with blockchain and its associated concepts and terminologies. You will explore the working mechanism of a decentralized application with the help of examples. Business leaders and blockchain enthusiasts will also find this book useful, as it will help you effectively address challenges and make better personal and business investments.
Apache Hadoop 3 Quick Start Guide: Learn about big data processing and analytics
by Hrishikesh Vijay KarambelkarA fast paced guide that will help you learn about Apache Hadoop 3 and its ecosystemKey FeaturesSet up, configure and get started with Hadoop to get useful insights from large data setsWork with the different components of Hadoop such as MapReduce, HDFS and YARN Learn about the new features introduced in Hadoop 3Book DescriptionApache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS.The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems.The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.What you will learnStore and analyze data at scale using HDFS, MapReduce and YARNInstall and configure Hadoop 3 in different modesUse Yarn effectively to run different applications on Hadoop based platformUnderstand and monitor how Hadoop cluster is managedConsume streaming data using Storm, and then analyze it using SparkExplore Apache Hadoop ecosystem components, such as Flume, Sqoop, HBase, Hive, and KafkaWho this book is forAspiring Big Data professionals who want to learn the essentials of Hadoop 3 will find this book to be useful. Existing Hadoop users who want to get up to speed with the new features introduced in Hadoop 3 will also benefit from this book. Having knowledge of Java programming will be an added advantage.