Write modern natural language processing applications using deep learning algorithms and TensorFlow About This Book ? Focuses on more efficient natural language processing using TensorFlow ? Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches ? Provides choices for how to process and evaluate large unstructured text datasets ? Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Who This Book Is For This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful. What You Will Learn ? Core concepts of NLP and various approaches to natural language processing ? How to solve NLP tasks by applying TensorFlow functions to create neural networks ? Strategies to process large amounts of data into word representations that can be used by deep learning applications ? Techniques for performing sentence classification and language generation using CNNs and RNNs ? About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks ? How to write automatic translation programs and implement an actual neural machine translator from scratch ? The trends and innovations that are paving the future in NLP In Detail Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. Style and approach The book provides an emphasis on both the theory and practice of natural language processing. It introduces the reader to existing TensorFlow functions and explains how to apply them while writing NLP algorithms. The popular Word2vec method is used to teach the essential process of learning word representations. The book focuses on how to apply classical deep learning to NLP, as well as exploring cutting edge and emerging approaches. Specific examples are used to make the concepts and techniques concrete.

A hands-on guide to creating, monitoring, and tuning a high performance Spring web application About This Book ? Understand common performance pitfalls and improve your application's performance ? Build and deploy strategies for complex applications using the microservice architecture ? Understand internals of JVM - the core of all Java Runtime Environments Who This Book Is For If you’re a Spring developer who’d like to build high performance applications and have more control over your application's performance in production and development, this book is for you. Some familiarity with Java, Maven, and Eclipse is necessary. What You Will Learn ? Master programming best practices and performance improvement with bean wiring ? Analyze the performance of various AOP implementations ? Explore database interactions with Spring to optimize design and configuration ? Solve Hibernate performance issues and traps ? Leverage multithreading and concurrent programming to improve application performance ? Gain a solid foundation in JVM performance tuning using various tools ? Learn the key concepts of the microservice architecture and how to monitor them ? Perform Spring Boot performance tuning, monitoring, and health checks In Detail While writing an application, performance is paramount. Performance tuning for real-world applications often involves activities geared toward detecting bottlenecks. The recent release of Spring 5.0 brings major advancements in the rich API provided by the Spring framework, which means developers need to master its tools and techniques to achieve high performance applications. Hands-On High Performance with Spring 5 begins with the Spring framework's core features, exploring the integration of different Spring projects. It proceeds to evaluate various Spring specifications to identify those adversely affecting performance. You will learn about bean wiring configurations, aspect-oriented programming, database interaction, and Hibernate to focus on the metrics that help identify performance bottlenecks. You will also look at application monitoring, performance optimization, JVM internals, and garbage collection optimization. Lastly, the book will show you how to leverage the microservice architecture to build a high performance and resilient application. By the end of the book, you will have gained an insight into various techniques and solutions to build and troubleshoot high performance Spring-based applications. Style and approach This book takes a step-by-step approach with focused examples to teach you how to increase application performance.

Discover how you can migrate a traditional on-premise SQL server database to a cloud-based solution with Microsoft Azure. Built with database administrators in mind, this book emulates different scenarios you might come across while working with large, complex SQL database migrations and provides solutions for effectively managing the migrated databases. Key Features *Implement backup, restore, and recovery of Azure SQL databases *Create shards and elastic pools to scale Azure SQL databases *Automate common management tasks with PowerShell *Implement over 40 practical activities and exercises across 24 topics to reinforce your learning Book Description As the cloud version of SQL Server, Azure SQL Database differs in key ways when it comes to management, maintenance, and administration. It’s important to know how to administer SQL Database to fully benefit from all of the features and functionality that it provides. This book addresses important aspects of an Azure SQL Database instance such as migration, backup restorations, pricing policies, security, scalability, monitoring, performance optimization, high availability, and disaster recovery. It is a complete guide for database administrators, and ideal for those who are planning to migrate from on premise SQL Server database to an Azure SQL Server database. What you will learn *Learn how to provision a new database or migrate an existing on-premise solution *Understand how to backup, restore, secure, and scale your own Azure SQL Database *Optimize the performance by monitoring and tuning your cloud-based SQL instance *Implement high availability and disaster recovery procedures with SQL Database *Develop a roadmap for your own scalable cloud solution with Azure SQL Database Who this book is for This book is ideal for database administrators, database developers, or application developers who are interested in developing or migrating existing applications with Azure SQL Database. Prior experience of working with an on-premise SQL Server deployment and brief knowledge of PowerShell and C# are recommended prerequisites.

Bridge the gap between developer and data scientist by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. Key Features *Think deeply as a developer about your strategy and toolset in data science *Discover the best tools that will suit you as a developer in your data analysis *Accelerate the road to data insight as a programmer using Jupyter Notebook *Deep dive into multiple industry data science use cases Book Description Thoughtful Data Science brings new strategies and a carefully crafted programmer's toolset to work with modern, cutting-edge data analysis. This new approach is designed specifically to give developers more efficiency and power to create cutting-edge data analysis and artificial intelligence insights. Industry expert David Taieb bridges the gap between developers and data scientists by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. You'll find the right balance of strategic thinking and practical projects throughout this book, with extensive code files and Jupyter projects that you can integrate with your own data analysis. David Taieb introduces four projects designed to connect developers to important industry use cases in data science. The first is an image recognition application with TensorFlow, to meet the growing importance of AI in data analysis. The second analyses social media trends to explore big data issues and natural language processing. The third is a financial portfolio analysis application using time series analysis, pivotal in many data science applications today. The fourth involves applying graph algorithms to solve data problems. Taieb wraps up with a deep look into the future of data science for developers and his views on AI for data science. What you will learn *Bridge the gap between developer and data scientist with a Python-based toolset *Get the most out of Jupyter Notebooks with new productivity-enhancing tools *Explore and visualize data using Jupyter Notebooks and PixieDust *Work with and assess the impact of artificial intelligence in data science *Work with TensorFlow, graphs, natural language processing, and time series *Deep dive into multiple industry data science use cases *Look into the future of data analysis and where to develop your skills Who this book is for This book is for established developers who want to bridge the gap between programmers and data scientists. With the introduction of PixieDust from its creator, the book will also be a great desk companion for the already accomplished Data Scientist. Some fluency in data interpretation and visualization is also assumed since this book addresses data professionals such as business and general data analysts. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. About This Book ? Get up and running with the Jupyter ecosystem and some example datasets ? Learn about key machine learning concepts like SVM, KNN classifiers and Random Forests ? Discover how you can use web scraping to gather and parse your own bespoke datasets Who This Book Is For This book is ideal for professionals with a variety of job descriptions across large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries like Pandas, Matplotlib and Pandas providing you a useful head start. What You Will Learn ? Identify potential areas of investigation and perform exploratory data analysis ? Plan a machine learning classification strategy and train classification models ? Use validation curves and dimensionality reduction to tune and enhance your models ? Scrape tabular data from web pages and transform it into Pandas DataFrames ? Create interactive, web-friendly visualizations to clearly communicate your findings In Detail Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Style and approach This book covers every aspect of the standard data-workflow process within a day, along with theory, practical hands-on coding, and relatable illustrations.

Install, Configure and Setup different connections with pfSense Key Features *Build firewall and routing solutions with PfSense. *Learn how to create captive portals, how to connect Pfsense to your https environment and so on. *Practical approach towards building firewall solutions for your organization Book Description As computer networks become ubiquitous, it has become increasingly important to both secure and optimize our networks. pfSense, an open-source router/firewall, provides an easy, cost-effective way of achieving this – and this book explains how to install and configure pfSense in such a way that even a networking beginner can successfully deploy and use pfSense. This book begins by covering networking fundamentals, deployment scenarios, and hardware sizing guidelines, as well as how to install pfSense. The book then covers configuration of basic services such as DHCP, DNS, and captive portal and VLAN configuration. Careful consideration is given to the core firewall functionality of pfSense, and how to set up firewall rules and traffic shaping. Finally, the book covers the basics of VPNs, multi-WAN setups, routing and bridging, and how to perform diagnostics and troubleshooting on a network. What you will learn *Install pfSense *Configure additional interfaces, and enable and configure DHCP *Understand Captive portal *Understand firewalls and NAT, and traffic shaping *Learn in detail about VPNs *Understand Multi-WAN *Learn about routing and bridging in detail *Understand the basics of diagnostics and troubleshooting networks Who this book is for This book is towards any network security professionals who want to get introduced to the world of firewalls and network configurations using Pfsense. No knowledge of PfSense is required

Get to grips with Kibana and its advanced functions to create interactive visualizations and dashboards Key Features *Explore visualizations and perform histograms, stats, and map analytics *Unleash X-Pack and Timelion, and learn alerting, monitoring, and reporting features *Manage dashboards with Beats and create machine learning jobs for faster analytics Book Description Kibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations. To begin with, Mastering Kibana 6.x quickly introduces you to the features of Kibana 6.x, before teaching you how to create smart dashboards in no time. You will explore metric analytics and graph exploration, followed by understanding how to quickly customize Kibana dashboards. In addition to this, you will learn advanced analytics such as maps, hits, and list analytics. All this will help you enhance your skills in running and comparing multiple queries and filters, influencing your data visualization skills at scale. With Kibana’s Timelion feature, you can analyze time series data with histograms and stats analytics. By the end of this book, you will have created a speedy machine learning job using X-Pack capabilities. What you will learn *Create unique dashboards with various intuitive data visualizations *Visualize Timelion expressions with added histograms and stats analytics *Integrate X-Pack with your Elastic Stack in simple steps *Extract data from Elasticsearch for advanced analysis and anomaly detection using dashboards *Build dashboards from web applications for application logs *Create monitoring and alerting dashboards using Beats Who this book is for Mastering Kibana 6.x is for you if you are a big data engineer, DevOps engineer, or data scientist aspiring to go beyond data visualization at scale and gain maximum insights from their large datasets. Basic knowledge of Elasticstack will be an added advantage, although not mandatory.

Learn to develop, test, and deploy your Spring Boot distributed application and explore various best practices. About This Book ? Build and deploy your microservices architecture in the cloud ? Build event-driven resilient systems using Hystrix and Turbine ? Explore API management tools such as KONG and API documentation tools such as Swagger Who This Book Is For The book is targeted at experienced Spring and Java developers who have a basic knowledge of working with Spring Boot. The reader should be familiar with Spring Boot basics, and aware of its benefits over traditional Spring Framework-based applications. What You Will Learn ? Build logically structured and highly maintainable Spring Boot applications ? Configure RESTful microservices using Spring Boot ? Make the application production and operation-friendly with Spring Actuator ? Build modern, high-performance distributed applications using cloud patterns ? Manage and deploy your Spring Boot application to the cloud (AWS) ? Monitor distributed applications using log aggregation and ELK In Detail Spring is one of the best frameworks on the market for developing web, enterprise, and cloud ready software. Spring Boot simplifies the building of complex software dramatically by reducing the amount of boilerplate code, and by providing production-ready features and a simple deployment model. This book will address the challenges related to power that come with Spring Boot's great configurability and flexibility. You will understand how Spring Boot configuration works under the hood, how to overwrite default configurations, and how to use advanced techniques to prepare Spring Boot applications to work in production. This book will also introduce readers to a relatively new topic in the Spring ecosystem – cloud native patterns, reactive programming, and applications. Get up to speed with microservices with Spring Boot and Spring Cloud. Each chapter aims to solve a specific problem or teach you a useful skillset. By the end of this book, you will be proficient in building and deploying your Spring Boot application. Style and approach The book takes a practical, example-driven approach to teaching you all the advanced features of Spring Boot 2.0

Find out how to write Kotlin code without overhead and how to use different profiling tools and bytecode viewer to inspect expressions of Kotlin language. About This Book ? Apply modern Kotlin features to speed up processing and implement highly efficient and reliable codes. ? Learn memory optimization, concurrency, multi-threading, scaling, and caching techniques to achieve high performance. ? Learn how to prevent unnecessary overhead and use profiling tools to detect performance issues. Who This Book Is For This book is for Kotlin developers who would like to build reliable and high-performance applications. Prior Kotlin programming knowledge is assumed. What You Will Learn ? Understand the importance of high performance ? Learn performance metrics ? Learn popular design patterns currently being used in Kotlin ? Understand how to apply modern Kotlin features to data processing ? Learn how to use profling tools ? Discover how to read bytecode ? Learn to perform memory optimizations ? Uncover approaches to the multithreading environment In Detail The ease with which we write applications has been increasing, but with it comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day requirement In this book, we explore how to achieve this crucial balance, while developing and deploying applications with Kotlin. The book starts by analyzing various Kotlin specifcations to identify those that have a potentially adverse effect on performance. Then, we move on to monitor techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help to us achieve high performance: memory optimization, concurrency, multi threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. We'll also cover best practices of Kotlin programming that will help you to improve the quality of your code base. By the end of the book, you will have gained some insight into various techniques and solutions that will help to create high-performance applications in the Kotlin environment Style and approach This book guides you through how to use profiling tools to detect performance issues and build high-performance applications in the Kotlin environment.

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. About This Book ? Explore deep reinforcement learning (RL), from the first principles to the latest algorithms ? Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms ? Keep up with the very latest industry developments, including AI-driven chatbots Who This Book Is For Some fluency in Python is assumed. Basic deep learning (DL) approaches should be familiar to readers and some practical experience in DL will be helpful. This book is an introduction to deep reinforcement learning (RL) and requires no background in RL. What You Will Learn ? Understand the DL context of RL and implement complex DL models ? Learn the foundation of RL: Markov decision processes ? Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others ? Discover how to deal with discrete and continuous action spaces in various environments ? Defeat Atari arcade games using the value iteration method ? Create your own OpenAI Gym environment to train a stock trading agent ? Teach your agent to play Connect4 using AlphaGo Zero ? Explore the very latest deep RL research on topics including AI-driven chatbots In Detail Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on 'grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. Style and approach Deep Reinforcement Learning Hands-On explains the art of building self-learning agents using algorithms and practical examples. Experiment with famous examples, such as Google's defeat of well-known Atari arcade games.

Unleash Google's Cloud Platform to build, train and optimize machine learning models About This Book ? Get well versed in GCP pre-existing services to build your own smart models ? A comprehensive guide covering aspects from data processing, analyzing to building and training ML models ? A practical approach to produce your trained ML models and port them to your mobile for easy access Who This Book Is For This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy What You Will Learn ? Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile ? Create, train and optimize deep learning models for various data science problems on big data ? Learn how to leverage BigQuery to explore big datasets ? Use Google’s pre-trained TensorFlow models for NLP, image, video and much more ? Create models and architectures for Time series, Reinforcement Learning, and generative models ? Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications In Detail Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. Style and approach An easy-to-follow step by step guide which will help you get to the grips with real-world applications of Google Cloud Machine Learning.

Get familiar with the building blocks of IoT solutions using off–the-shelf IoT platforms. About This Book ? Work with various trending IoT platforms such as AWS IoT, Azure IoT, Google IoT, IBM Watson IoT, and Kaa IoT ? Gain hands-on knowledge working with Cloud-based IoT platforms, IoT Analytics, and so on. ? A practical guide that will help you build IoT strategies for your organization Who This Book Is For This book is targeted at IoT architects and engineers, or any stakeholders working with IoT solutions in an organization. This book will also help decision makers and professionals from small- and medium-sized enterprises build an IoT strategy for their venture. What You Will Learn ? Connect a Temperature and Humidity sensor and see how these two can be managed from various platforms ? Explore the core components of AWS IoT such as AWS Kinesis and AWS IoTRules Engine ? Build a simple analysis dashboard using Azure IoT and Power BI ? Understand the fundamentals of Google IoT and use Google core APIs to build your own dashboard ? Get started and work with the IBM Watson IoT platform ? Integrate Cassandra and Zeppelin with Kaa IoT dashboard ? Review some Machine Learning and AI and get to know more about their implementation in the IoT domain. In Detail There is a lot of work that is being done in the IoT domain and according to Forbes the global IoT market will grow from $157B in 2016 to $457B by 2020. This is an amazing market both in terms technology advancement as well as money. In this book, we will be covering five popular IoT platforms, namely, AWS IoT, Microsoft Azure IoT, Google IoT Core, IBM Watson IoT, and Kaa IoT middleware. You are going to build solutions that will use a Raspberry Pi 3, a DHT11 Temperature and humidity sensor, and a dashboard to visualize the sensor data in real-time. Furthermore, you will also explore various components of each of the platforms that are needed to achieve the desired solution. Besides building solutions, you will look at how Machine Learning and IoT go hand in hand and later design a simple predictive web service based on this concept. By the end of this book, you will be in a position to implement an IoT strategy best-fit for your organization Style and approach An informative guide that will help you design and implement an IoT Strategy best-fit for your organization

Integrate an end-to-end logistic chain using IBM Blockchain and IoT platforms Key Features *Explore practical implementation of ledger technology in the IoT architecture *Study security best practices for your smart devices *Understand Blockchain implementation for end-to-end IoT solutions Book Description Blockchain has been the hot topic of late thanks to cryptocurrencies. To make matters more interesting, the financial market is looking for ways to reduce operational costs and generate new business models, and this is where blockchain solutions come into the picture. In addition to this, with Internet of Things (IoT) trending and Arduino, Raspberry Pi, and other devices flooding the market, you can now create cheap devices even at home. Hands-On IoT Solutions with Blockchain starts with an overview of IoT concepts in the current business scenario. It then helps you develop your own device on the IBM Watson IoT platform and create your fi rst IoT solution using Watson and Intel Edison.Once you are familiar with IoT, you will learn about Blockchain technology and its use cases. You will also work with the Hyperledger framework and develop your own Blockchain network. As you progress through the chapters, you'll work with problem statements and learn how to design your solution architecture so that you can create your own integrated Blockchain and IoT solution. The next set of chapters will explain how to implement end-to-end Blockchain solutions with IoT using the IBM Cloud platform. By the end of this book, you will have mastered the convergence of IoT and Blockchain technology and exploited the best practices and drivers to develop a bulletproof integrated solution. What you will learn *Understand the key roles of IoT in the current market *Study the different aspects of IBM Watson IoT platform *Create devices, gateways, and applications connected to the platform *Explore the fundamentals of Blockchain *Define good use cases for Blockchain *Discover the Hyperledger Fabric and Composer frameworks *Develop an IBM Watson IoT application using a Intel Edison *Integrate IoT with the Blockchain platform Who this book is for Hands-On IoT Solutions with Blockchain is for you if you are an Internet of Things (IoT) analyst, architect, engineer, or any stakeholder responsible for security mechanisms on an IoT infrastructure. This book is also for IT professionals who want to start developing solutions using Blockchain and IoT on the IBM Cloud platform. Basic understanding of IoT will assist you in understanding key concepts covered in the book.

An in-depth and comprehensive take on WordPress, covering everything about the platform such as WordPress posts, pages, themes, plugins, and more. Key Features * Get up to date with the latest WordPress 5.0 (Bebo) and all its new features * Beginner-friendly layout and advice you can apply from day one with loads of screenshots and examples * Enrich your development experience with the new block-based editor Gutenberg Book Description Back in the day, when you wanted to launch a new website, you either had to learn web programming yourself or hire a professional who would take care of the whole process for you. Nowadays, with WordPress, anyone can build an optimized site with the least amount of effort possible and then make it available to the world in no time. Here, in the seventh edition of the book, we are going to show you how to build great looking and functional websites using WordPress. The new version of WordPress – 5.0 – comes with a few important changes, and we tell you all about how to use them effectively. From crafting content pages using the block editor, and customizing the design of your site, through to making sure it's secure, we go through it all. The book starts by introducing WordPress and teaching you how to set it up. You are then shown how to create a blog site, start writing content, and even use plugins and themes to customize the design of the site and add some unique elements to set it apart. If you want to get more in-depth, we also show you how to get started creating your own themes and plugins. Finally, we teach you how to use WordPress for building non-blog websites. By the end of the book, you will be sufficiently skilled to design high-quality websites and will be fully familiar with the ins and outs of WordPress. What you will learn * Learn to adapt your plugin with the Gutenberg editor * Create content that is optimized for publication on the web * Craft great looking pages and posts with the use of block editor * Structure your web pages in an accessible and clear way * Install and work with plugins and themes * Customize the design of your website * Upload multimedia content, such as images, audio, and video easily and effectively * Develop your own WordPress plugins and themes * Use WordPress to build websites that serve purposes other than blogs Who this book is for The ideal target audience for this book would be PHP developers who have some basic knowledge of working with WordPress and who want to get a comprehensive practical understanding of working with WordPress and create production-ready websites with it.

Discover end-to-end penetration testing solutions to enhance your ethical hacking skills Key Features * Practical recipes to conduct effective penetration testing using the latest version of Kali Linux * Leverage tools like Metasploit, Wireshark, Nmap, and more to detect vulnerabilities with ease * Confidently perform networking and application attacks using task-oriented recipes Book Description Many organizations have been affected by recent cyber events. At the current rate of hacking, it has become more important than ever to pentest your environment in order to ensure advanced-level security. This book is packed with practical recipes that will quickly get you started with Kali Linux (version 2018.4 / 2019), in addition to covering the core functionalities. The book will get you off to a strong start by introducing you to the installation and configuration of Kali Linux, which will help you to perform your tests. You will also learn how to plan attack strategies and perform web application exploitation using tools such as Burp and JexBoss. As you progress, you will get to grips with performing network exploitation using Metasploit, Sparta, and Wireshark. The book will also help you delve into the technique of carrying out wireless and password attacks using tools such as Patator, John the Ripper, and airoscript-ng. Later chapters will draw focus to the wide range of tools that help in forensics investigations and incident response mechanisms. As you wrap up the concluding chapters, you will learn to create an optimum quality pentest report. By the end of this book, you will be equipped with the knowledge you need to conduct advanced penetration testing, thanks to the book’s crisp and task-oriented recipes. What you will learn * Learn how to install, set up and customize Kali for pentesting on multiple platforms * Pentest routers and embedded devices * Get insights into fiddling around with software-defined radio * Pwn and escalate through a corporate network * Write good quality security reports * Explore digital forensics and memory analysis with Kali Linux Who this book is for If you are an IT security professional, pentester, or security analyst who wants to conduct advanced penetration testing techniques, then this book is for you. Basic knowledge of Kali Linux is assumed.

Leverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasks Key Features * Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python * Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving. * Formulate and devise selective algorithms and techniques in your applications in no time. Book Description Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving. The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator. By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems. What you will learn * Understand the theory and concepts behind modern Reinforcement Learning algorithms * Code state-of-the-art Reinforcement Learning algorithms with discrete or continuous actions * Develop Reinforcement Learning algorithms and apply them to training agents to play computer games * Explore DQN, DDQN, and Dueling architectures to play Atari's Breakout using TensorFlow * Use A3C to play CartPole and LunarLander * Train an agent to drive a car autonomously in a simulator Who this book is for Data scientists and AI developers who wish to quickly get started with training effective reinforcement learning models in TensorFlow will find this book very useful. Prior knowledge of machine learning and deep learning concepts (as well as exposure to Python programming) will be useful.

Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key Features * Assimilate key NLP concepts and terminologies * Explore popular NLP tools and techniques * Gain practical experience using NLP in application code Book Description If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language. What you will learn * Obtain, verify, and clean data before transforming it into a correct format for use * Perform data analysis and machine learning tasks using Python * Understand the basics of computational linguistics * Build models for general natural language processing tasks * Evaluate the performance of a model with the right metrics * Visualize, quantify, and perform exploratory analysis from any text data Who this book is for Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.

Achieve improved network programmability and automation by leveraging powerful network programming concepts, algorithms, and tools Key Features * Deal with remote network servers using SSH, FTP, SNMP and LDAP protocols. * Design multi threaded and event-driven architectures for asynchronous servers programming. * Leverage your Python programming skills to build powerful network applications Book Description Network programming has always been a demanding task. With full-featured and well-documented libraries all the way up the stack, Python makes network programming the enjoyable experience it should be. Starting with a walk through of today's major networking protocols, through this book, you'll learn how to employ Python for network programming, how to request and retrieve web resources, and how to extract data in major formats over the web. You will utilize Python for emailing using different protocols, and you'll interact with remote systems and IP and DNS networking. You will cover the connection of networking devices and configuration using Python 3.7, along with cloud-based network management tasks using Python. As the book progresses, socket programming will be covered, followed by how to design servers, and the pros and cons of multithreaded and event-driven architectures. You'll develop practical clientside applications, including web API clients, email clients, SSH, and FTP. These applications will also be implemented through existing web application frameworks. What you will learn * Execute Python modules on networking tools * Automate tasks regarding the analysis and extraction of information from a network * Get to grips with asynchronous programming modules available in Python * Get to grips with IP address manipulation modules using Python programming * Understand the main frameworks available in Python that are focused on web application * Manipulate IP addresses and perform CIDR calculations Who this book is for If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. If you're a network engineer or a network professional aiming to be more productive and efficient in networking programmability and automation then this book would serve as a useful resource. Basic knowledge of Python is assumed.

Design, develop, and solve real-world automation and orchestration problems by unlocking the automation capabilities of Ansible. Key Features * Tackle complex automation challenges with the newly added features in Ansible 2.7 Book Description Automation is essential for success in the modern world of DevOps. Ansible provides a simple, yet powerful, automation engine for tackling complex automation challenges. This book will take you on a journey that will help you exploit the latest version's advanced features to help you increase efficiency and accomplish complex orchestrations. This book will help you understand how Ansible 2.7 works at a fundamental level and will also teach you to leverage its advanced capabilities. Throughout this book, you will learn how to encrypt Ansible content at rest and decrypt data at runtime. Next, this book will act as an ideal resource to help you master the advanced features and capabilities required to tackle complex automation challenges. Later, it will walk you through workflows, use cases, orchestrations, troubleshooting, and Ansible extensions. Lastly, you will examine and debug Ansible operations, helping you to understand and resolve issues. By the end of the book, you will be able to unlock the true power of the Ansible automation engine and tackle complex, real- world actions with ease. What you will learn * Gain an in-depth understanding of how Ansible works under the hood * Fully automate Ansible playbook executions with encrypted data * Access and manipulate variable data within playbooks * Use blocks to perform failure recovery or cleanup * Explore the Playbook debugger and the Ansible Console * Troubleshoot unexpected behavior effectively * Work with cloud infrastructure providers and container systems * Develop custom modules, plugins, and dynamic inventory sources Who this book is for This book is for Ansible developers and operators who have an understanding of its core elements and applications but are now looking to enhance their skills in applying automation using Ansible.

Explore various Azure services to build solutions that leverage effective design patterns Key Features *Create, deploy, and host cloud applications on Azure *Understand various Azure services that help you host serverless applications *Explore practical examples to help you secure and troubleshoot your cloud environment Book Description Azure is one of the leading public cloud service providers. Thanks to a number of Azure service updates, it continues to make advances in the realm of cloud computing. Learn Microsoft Azure starts with the fundamentals of cloud computing. You will learn to configure and set up the Azure infrastructure. As you make your way through the book, you'll explore Azure services, along with working on virtual memory systems (VMS) and deployment models. You will understand various services in the Azure ecosystem, such as Azure IoT and Azure Analytics, among others. An easy-to-follow introduction to various cloud design patterns will also add to your efficiency in designing cloud solutions. In the concluding chapters, you'll secure your virtual networks using Network security groups and configure Azure Active Directory (Azure AD) to set a custom domain name and company profile. By the end of this book, you will have learned to secure and troubleshoot your Azure cloud environment and be fully aware of best practices for Azure cloud administration. What you will learn *Understand the cloud services offered by Azure *Design storage and networks in Azure for your Azure VM *Work with web apps and Azure SQL databases *Build your identity management solutions on Azure using Azure AD *Monitor, protect, and automate your Azure services using Operation Management Suite (OMS) *Implement OMS for Azure services Who this book is for Learn Microsoft Azure is for administrators, cloud engineers, and developers who want to get started with using Azure as their cloud platform and build cloud-based applications for their enterprises.

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key Features *Work with powerful open-source libraries for data wrangling, analysis, and visualization *Develop full-featured, full-stack web applications *Learn to perform supervised and unsupervised machine learning and time series analysis with Julia Book Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learn *Leverage Julia's strengths, its top packages, and main IDE options *Analyze and manipulate datasets using Julia and DataFrames *Write complex code while building real-life Julia applications *Develop and run a web app using Julia and the HTTP package *Build a recommender system using supervised machine learning *Perform exploratory data analysis *Apply unsupervised machine learning algorithms *Perform time series data analysis, visualization, and forecasting Who this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.