Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features *Implement machine learning algorithms to build, train, and validate algorithmic models *Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions *Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn *Implement machine learning techniques to solve investment and trading problems *Leverage market, fundamental, and alternative data to research alpha factors *Design and fine-tune supervised, unsupervised, and reinforcement learning models *Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn *Integrate machine learning models into a live trading strategy on Quantopian *Evaluate strategies using reliable backtesting methodologies for time series *Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow *Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks Key Features *Understand the foundations of meta learning algorithms *Explore practical examples to explore various one-shot learning algorithms with its applications in TensorFlow *Master state of the art meta learning algorithms like MAML, reptile, meta SGD Book Description Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster. Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning. By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models. What you will learn *Understand the basics of meta learning methods, algorithms, and types *Build voice and face recognition models using a siamese network *Learn the prototypical network along with its variants *Build relation networks and matching networks from scratch *Implement MAML and Reptile algorithms from scratch in Python *Work through imitation learning and adversarial meta learning *Explore task agnostic meta learning and deep meta learning Who this book is for Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.

Speed up the design and implementation of deep learning solutions using Apache Spark Key Features * Explore the world of distributed deep learning with Apache Spark * Train neural networks with deep learning libraries such as BigDL and TensorFlow * Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn * Understand the basics of deep learning * Set up Apache Spark for deep learning * Understand the principles of distribution modeling and different types of neural networks * Obtain an understanding of deep learning algorithms * Discover textual analysis and deep learning with Spark * Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras * Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

Implement defensive techniques in your ecosystem successfully with Python Key Features * Identify and expose vulnerabilities in your infrastructure with Python * Learn custom exploit development . * Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn * Get to grips with Custom vulnerability scanner development * Familiarize yourself with web application scanning automation and exploit development * Walk through day-to-day cybersecurity scenarios that can be automated with Python * Discover enterprise-or organization-specific use cases and threat-hunting automation * Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. * Understand web scraping in Python and use it for processing web responses * Explore Security Operations Centre (SOC) use cases * Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure .

Build applications and infrastructures that leverage Function-as-a-Service and Docker About This Book ? Implement containerization in Serverless/FaaS environments ? Utilize Docker as a functional unit of work for Serverless/FaaS platforms ? Use Docker as a portable infrastructure for Serverless Applications Who This Book Is For If you are a Developer, a Docker Engineer, a DevOps Engineer, or any stakeholder interested in learning the use of Docker on Serverless environments then this book is for you. What You Will Learn ? Learn what Serverless and FaaS applications are ? Get acquainted with the architectures of three major serverless systems ? Explore how Docker technologies can help develop Serverless applications ? Create and maintain FaaS infrastructures ? Set up Docker infrastructures to serve as on-premises FaaS infrastructures ? Define functions for Serverless applications with Docker containers In Detail Serverless applications have gained a lot of popularity among developers and are currently the buzzwords in the tech market. Docker and serverless are two terms that go hand-in-hand. This book will start by explaining serverless and Function-as-a-Service (FaaS) concepts, and why they are important. Then, it will introduce the concepts of containerization and how Docker fits into the Serverless ideology. It will explore the architectures and components of three major Docker-based FaaS platforms, how to deploy and how to use their CLI. Then, this book will discuss how to set up and operate a production-grade Docker cluster. We will cover all concepts of FaaS frameworks with practical use cases, followed by deploying and orchestrating these serverless systems using Docker. Finally, we will also explore advanced topics and prototypes for FaaS architectures in the last chapter. By the end of this book, you will be in a position to build and deploy your own FaaS platform using Docker. Style and approach A practical guide that offers a simple way to easily understand Serverless Applications utilizing Docker as the development environment.

Learn the most powerful and primary programming language for writing smart contracts and find out how to write, deploy, and test smart contracts in Ethereum. About This Book ? Get you up and running with Solidity Programming language ? Build Ethereum Smart Contracts with Solidity as your scripting language ? Learn to test and deploy the smart contract to your private Blockchain Who This Book Is For This book is for anyone who would like to get started with Solidity Programming for developing an Ethereum smart contract. No prior knowledge of EVM is required. What You Will Learn ? Learn the basics and foundational concepts of Solidity and Ethereum ? Explore the Solidity language and its uniqueness in depth ? Create new accounts and submit transactions to blockchain ? Get to know the complete language in detail to write smart contracts ? Learn about major tools to develop and deploy smart contracts ? Write defensive code using exception handling and error checking ? Understand Truffle basics and the debugging process In Detail Solidity is a contract-oriented language whose syntax is highly influenced by JavaScript, and is designed to compile code for the Ethereum Virtual Machine. Solidity Programming Essentials will be your guide to understanding Solidity programming to build smart contracts for Ethereum and blockchain from ground-up. We begin with a brief run-through of blockchain, Ethereum, and their most important concepts or components. You will learn how to install all the necessary tools to write, test, and debug Solidity contracts on Ethereum. Then, you will explore the layout of a Solidity source file and work with the different data types. The next set of recipes will help you work with operators, control structures, and data structures while building your smart contracts. We take you through function calls, return types, function modifers, and recipes in object-oriented programming with Solidity. Learn all you can on event logging and exception handling, as well as testing and debugging smart contracts. By the end of this book, you will be able to write, deploy, and test smart contracts in Ethereum. This book will bring forth the essence of writing contracts using Solidity and also help you develop Solidity skills in no time. Style and approach Solidity is a high-level programming language best understood using examples. After covering basic concepts of Ethereum and Solidity, programming constructs will be explained with help of examples. As chapters progress, deployment, usage and testing of contacts will form major aspect of the book. Troubleshooting and unit testing is an important exercise and skill to master this language will also be covered in this book.

Explore GIS processing and learn to work with various tools and libraries in Python. About This Book ? Analyze and process geospatial data using Python libraries such as; Anaconda, GeoPandas ? Leverage new ArcGIS API to process geospatial data for the cloud. ? Explore various Python geospatial web and machine learning frameworks. Who This Book Is For The audience for this book includes students, developers, and geospatial professionals who need a reference book that covers GIS data management, analysis, and automation techniques with code libraries built in Python 3. What You Will Learn ? Manage code libraries and abstract geospatial analysis techniques using Python 3. ? Explore popular code libraries that perform specific tasks for geospatial analysis. ? Utilize code libraries for data conversion, data management, web maps, and REST API creation. ? Learn techniques related to processing geospatial data in the cloud. ? Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and SpatiaLite. In Detail Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API. Style and approach The book takes a practical, example-driven approach to teach you GIS analysis and automation techniques with Python 3.

Practical, hands-on solutions in Python to overcome any problem in Machine Learning About This Book ? Master the advanced concepts, methodologies, and use cases of machine learning ? Build ML applications for analytics, NLP and computer vision domains ? Solve the most common problems in building machine learning models Who This Book Is For This book is for the intermediate users such as machine learning engineers, data engineers, data scientists, and more, who want to solve simple to complex machine learning problems in their day-to-day work and build powerful and efficient machine learning models. A basic understanding of the machine learning concepts and some experience with Python programming is all you need to get started with this book. What You Will Learn ? Select the right algorithm to derive the best solution in ML domains ? Perform predictive analysis effciently using ML algorithms ? Predict stock prices using the stock index value ? Perform customer analytics for an e-commerce platform ? Build recommendation engines for various domains ? Build NLP applications for the health domain ? Build language generation applications using different NLP techniques ? Build computer vision applications such as facial emotion recognition In Detail Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions. In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity. Style and approach This book is a step-by-step guide on how to develop machine learning applications for various domains. Each chapter of this book contains the practical guide on how to build specific machine learning applications from its base-line approach to the best possible approach. Basic necessary concepts, conman mistakes for every approach and optimization techniques are discussed for each application.

Get 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 objectives About This Book ? Learn to successfully design and architect powerful solutions on the Azure Cloud platform ? Enhance your skills with mock tests and practice questions ? A detailed certification guide that will help you ace the 70-535 exam with confidence Who This Book Is For This 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. What You Will Learn ? Use Azure Virtual Machines to design effective VM deployments ? Implement architecture styles, like serverless computing and microservices ? Secure your data using different security features and design effective security strategies ? Design Azure storage solutions using various storage features ? Create identity management solutions for your applications and resources ? Architect state-of-the-art solutions using Artificial Intelligence, IoT, and Azure Media Services ? Use different automation solutions that are incorporated in the Azure platform In Detail Architecting 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. Style and approach This book offers clear and crisp explanations of the exam objectives that will help you with all the information needed to pass the 70-535 exam. The detail oriented approach will make you an expert on designing solutions on Microsoft Azure.

Unleash the power of the Raspberry Pi 3 board to create interesting IoT projects About This Book ? Learn how to interface various sensors and actuators with the Raspberry Pi 3 and send this data to the cloud. ? Explore the possibilities offered by the IoT by using the Raspberry Pi to upload measurements to Google Docs. ? A practical guide that will help you create a Raspberry Pi robot using IoT modules. Who This Book Is For If you're a developer or electronics engineer and are curious about the Internet of Things, then this is the book for you. With only a rudimentary understanding of electronics, the Raspberry Pi, or similar credit-card sized computers, and some programming experience, you will be taught to develop state-of-the-art solutions for the Internet of Things in an instant. What You Will Learn ? Understand the concept of IoT and get familiar with the features of Raspberry Pi ? Learn to integrate sensors and actuators with the Raspberry Pi ? Communicate with cloud and Raspberry using communication protocols such as HTTP and MQTT ? Build DIY projects using Raspberry Pi, JavaScript/node.js and cloud (AWS) ? Explore the best practices to ensure the security of your connected devices In Detail This book is designed to introduce you to IoT and Raspberry Pi 3. It will help you create interesting projects, such as setting up a weather station and measuring temperature and humidity using sensors; it will also show you how to send sensor data to cloud for visualization in real-time. Then we shift our focus to leveraging IoT for accomplishing complex tasks, such as facial recognition using the Raspberry Pi camera module, AWS Rekognition, and the AWS S3 service. Furthermore, you will master security aspects by building a security surveillance system to protect your premises from intruders using Raspberry Pi, a camera, motion sensors, and AWS Cloud. We'll also create a real-world project by building a Wi-Fi – controlled robot car with Raspberry Pi using a motor driver circuit, DC motor, and a web application. This book is a must-have as it provides a practical overview of IoT’s existing architectures, communication protocols, and security threats at the software and hardware levels—security being the most important aspect of IoT. Style and approach Internet of Things with the Raspberry Pi 3 contains the tools needed to design, sense the environment, communicate over the Internet, and visualize the results.

This book teaches you everything you need to know to create stunning Vaadin applications for all your web development needs. Deep dive into advanced Vaadin concepts while creating your very own sample Vaadin application. About This Book ? A one-stop book to enhance your working knowledge with Vaadin. ? Explore and implement the architecture of Vaadin applications. ? Delve into advanced topics such as data binding, authentication and authorization to improvise your application’s performance. Who This Book Is For If you area Software developer with previous experience with Vaadin and would like to gain more comprehensive and advanced skills in Vaadin web development, then this book is for you. What You Will Learn ? Modularize your Vaadin applications with Maven ? Create high quality custom components ? Implement robust and secure authentication and authorization mechanisms ? Connect to SQL databases efficiently ? Design robust CRUD (Create, Read, Update, Delete) views ? Generate stunning reports ? Improve resource consumption by using lazy loading In Detail Vaadin is an open-source Java framework used to build modern user interfaces. Vaadin 8 simplifies application development and improves user experience. The book begins with an overview of the architecture of Vaadin applications and the way you can organize your code in modules.Then it moves to the more advanced topics about advanced topics such as internationalization, authentication, authorization, and database connectivity. The book also teaches you how to implement CRUD views, how to generate printable reports, and how to manage data with lazy loading. By the end of this book you will be able to architect, implement, and deploy stunning Vaadin applications, and have the knowledge to master web development with Vaadin. Style and approach This book follows a hands-on approach and takes the readers through practical examples of how to create and deploy Vaadin applications. This book teaches the readers about the Vaadin architecture. It then moves on to the more advanced topics about advanced topics such as internationalization, authentication, authorization, and database connectivity. This step by step guide equips the readers with all they need to know to use Vaadin for web development.

Leverage the power of PostgreSQL 10 to design, administer and maintain a high-performance database solution About This Book ? Obtain optimal PostgreSQL 10 database performance, ranging from initial design to routine maintenance ? Fine tune the performance of your queries and avoid the common pitfalls that can slow your system down ? Contains tips and tricks on scaling successful database installations, and ensuring a highly available PostgreSQL solution Who This Book Is For This book is designed for database administrators and PostgreSQL architects who already use or plan to exploit the features of PostgreSQL 10 to design and maintain a high-performance PostgreSQL database. A working knowledge of SQL, and some experience with PostgreSQL will be helpful in getting the most out of this book. What You Will Learn ? Learn best practices for scaling PostgreSQL 10 installations ? Discover the best hardware for developing high-performance PostgreSQL applications ? Benchmark your whole system – from hardware to application ? Learn by real examples how server parameters impact performance ? Discover PostgreSQL 10 features for partitioning and parallel query ? Monitor your server, both inside and outside the database ? Design and implement a good replication system on PostgreSQL 10 In Detail PostgreSQL database servers have a common set of problems that they encounter as their usage gets heavier and requirements get more demanding. Peek into the future of your PostgreSQL 10 database's problems today. Know the warning signs to look for and how to avoid the most common issues before they even happen. Surprisingly, most PostgreSQL database applications evolve in the same way—choose the right hardware, tune the operating system and server memory use, optimize queries against the database and CPUs with the right indexes, and monitor every layer, from hardware to queries, using tools from inside and outside PostgreSQL. Also, using monitoring insight, PostgreSQL database applications continuously rework the design and configuration. On reaching the limits of a single server, they break things up; connection pooling, caching, partitioning, replication, and parallel queries can all help handle increasing database workloads. By the end of this book, you will have all the knowledge you need to design, run, and manage your PostgreSQL solution while ensuring high performance and high availability Style and approach This book has been organized in such a manner that will help you understand basic PostgreSQL 10 performance tuning to an advanced-level configuration.

Design and implement scalable and maintainable RESTful solutions with Node.js 10 About This Book ? Create rich and scalable RESTful API solutions from scratch ? Explore the new features of Node.js 10, Express 4.0, and MongoDB ? Integrate MongoDB in your Node.js application to store and secure your data Who This Book Is For If you are a web developer keen to enrich your development skills to create server-side RESTful applications based on the Node.js platform, this book is for you. Some knowledge of REST would be an added advantage, but is definitely not a necessity. What You Will Learn ? Install, develop, and test your own Node.js user modules ? Understand the differences between HTTP and RESTful applications ? Use self-descriptive URLs and set accurate HTTP status codes ? Eliminate third-party dependencies in your tests with mocking ? Implement automation tests for a REST-enabled endpoint with Mocha ? Secure your services with NoSQL database integration within Node.js applications ? Integrate a simple frontend using JavaScript libraries available on a CDN server In Detail When building RESTful services, it is really important to choose the right framework. Node.js, with its asynchronous, event-driven architecture, is exactly the right choice for building RESTful APIs. This third edition of RESTful Web API Design with Node.js 10 will teach you to create scalable and rich RESTful applications based on the Node.js platform. You will be introduced to the latest NPM package handler and understand how to use it to customize your RESTful development process. You will begin by understanding the key principle that makes an HTTP application a RESTful-enabled application. After writing a simple HTTP request handler, you will create and test Node.js modules using automated tests and mock objects; explore using the NoSQL database, MongoDB, to store data; and get to grips with using self-descriptive URLs. You’ll learn to set accurate HTTP status codes along with understanding how to keep your applications backward-compatible. Also, while implementing a full-fledged RESTful service, you will use Swagger to document the API and implement automation tests for a REST-enabled endpoint with Mocha. Lastly, you will explore some authentication techniques to secure your application. Style and approach Step-by-step practical guide to building RESTful applications

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Explore powerful R packages to create predictive models using ensemble methods Key Features *Implement machine learning algorithms to build ensemble-efficient models *Explore powerful R packages to create predictive models using ensemble methods *Learn to build ensemble models on large datasets using a practical approach Book Description Ensemble techniques are used for combining two or more similar or dissimilar machine learning algorithms to create a stronger model. Such a model delivers superior prediction power and can give your datasets a boost in accuracy. Hands-On Ensemble Learning with R begins with the important statistical resampling methods. You will then walk through the central trilogy of ensemble techniques – bagging, random forest, and boosting – then you'll learn how they can be used to provide greater accuracy on large datasets using popular R packages. You will learn how to combine model predictions using different machine learning algorithms to build ensemble models. In addition to this, you will explore how to improve the performance of your ensemble models. By the end of this book, you will have learned how machine learning algorithms can be combined to reduce common problems and build simple efficient ensemble models with the help of real-world examples. What you will learn *Carry out an essential review of re-sampling methods, bootstrap, and jackknife *Explore the key ensemble methods: bagging, random forests, and boosting *Use multiple algorithms to make strong predictive models *Enjoy a comprehensive treatment of boosting methods *Supplement methods with statistical tests, such as ROC *Walk through data structures in classification, regression, survival, and time series data *Use the supplied R code to implement ensemble methods *Learn stacking method to combine heterogeneous machine learning models Who this book is for This book is for you if you are a data scientist or machine learning developer who wants to implement machine learning techniques by building ensemble models with the power of R. You will learn how to combine different machine learning algorithms to perform efficient data processing. Basic knowledge of machine learning techniques and programming knowledge of R would be an added advantage.

Use an open source firewall and features such as failover, load balancer, OpenVPN, IPSec, and Squid to protect your network Key Features *Explore pfSense, a trusted open source network security solution *Configure pfSense as a firewall and create and manage firewall rules *Test pfSense for failover and load balancing across multiple WAN connections Book Description While connected to the internet, you’re a potential target for an array of cyber threats, such as hackers, keyloggers, and Trojans that attack through unpatched security holes. A firewall works as a barrier (or ‘shield’) between your computer and cyberspace. pfSense is highly versatile firewall software. With thousands of enterprises using pfSense, it is fast becoming the world's most trusted open source network security solution. Network Security with pfSense begins with an introduction to pfSense, where you will gain an understanding of what pfSense is, its key features, and advantages. Next, you will learn how to configure pfSense as a firewall and create and manage firewall rules. As you make your way through the chapters, you will test pfSense for failover and load balancing across multiple wide area network (WAN) connections. You will then configure pfSense with OpenVPN for secure remote connectivity and implement IPsec VPN tunnels with pfSense. In the concluding chapters, you’ll understand how to configure and integrate pfSense as a Squid proxy server. By the end of this book, you will be able to leverage the power of pfSense to build a secure network. What you will learn *Understand what pfSense is, its key features, and advantages *Configure pfSense as a firewall *Set up pfSense for failover and load balancing *Connect clients through an OpenVPN client *Configure an IPsec VPN tunnel with pfSense *Integrate the Squid proxy into pfSense Who this book is for Network Security with pfSense is for IT administrators, security administrators, technical architects, chief experience officers, and individuals who own a home or small office network and want to secure it.

Over 60 recipes to help you design interactive, smart, and cross-platform GUI applications Key Features * Get succinct QT solutions to pressing GUI programming problems in Python * Learn how to effectively implement reactive programming * Build customized applications that are robust and reliable Book Description PyQt is one of the best cross-platform interface toolkits currently available; it's stable, mature, and completely native. If you want control over all aspects of UI elements, PyQt is what you need. This book will guide you through every concept necessary to create fully functional GUI applications using PyQt, with only a few lines of code. As you expand your GUI using more widgets, you will cover networks, databases, and graphical libraries that greatly enhance its functionality. Next, the book guides you in using Qt Designer to design user interfaces and implementing and testing dialogs, events, the clipboard, and drag and drop functionality to customize your GUI. You will learn a variety of topics, such as look and feel customization, GUI animation, graphics rendering, implementing Google Maps, and more. Lastly, the book takes you through how Qt5 can help you to create cross-platform apps that are compatible with Android and iOS. You will be able to develop functional and appealing software using PyQt through interesting and fun recipes that will expand your knowledge of GUIs What you will learn * Use basic Qt components, such as a radio button, combo box, and sliders * Use QSpinBox and sliders to handle different signals generated on mouse clicks * Work with different Qt layouts to meet user interface requirements * Create custom widgets and set up customizations in your GUI * Perform asynchronous I/O operations and thread handling in the Python GUI * Employ network concepts, internet browsing, and Google Maps in UI * Use graphics rendering and implement animation in your GUI * Make your GUI application compatible with Android and iOS devices Who this book is for If you’re an intermediate Python programmer wishing to enhance your coding skills by writing powerful GUIs in Python using PyQT, this is the book for you.

Learn the fundamentals of Java EE 8 APIs to build effective web services Key Features *Design modern and stylish web services with Java EE APIs *Secure your web services with JSON Web Tokens *Explore the advanced concepts of RESTful web services and the JAX-RS API Book Description Java Enterprise Edition is one of the leading application programming platforms for enterprise Java development. With Java EE 8 finally released and the first application servers now available, it is time to take a closer look at how to develop modern and lightweight web services with the latest API additions and improvements. Building RESTful Web Services with Java EE 8 is a comprehensive guide that will show you how to develop state-of-the-art RESTful web services with the latest Java EE 8 APIs. You will begin with an overview of Java EE 8 and the latest API additions and improvements. You will then delve into the details of implementing synchronous RESTful web services and clients with JAX-RS. Next up, you will learn about the specifics of data binding and content marshalling using the JSON-B 1.0 and JSON-P 1.1 APIs. This book also guides you in leveraging the power of asynchronous APIs on the server and client side, and you will learn to use server-sent events (SSEs) for push communication. The final section covers advanced web service topics such as validation, JWT security, and diagnosability. By the end of this book, you will have implemented several working web services and have a thorough understanding of the Java EE 8 APIs required for lightweight web service development. What you will learn *Dive into the latest Java EE 8 APIs relevant for developing web services *Use the new JSON-B APIs for easy data binding *Understand how JSON-P API can be used for flexible processing *Implement synchronous and asynchronous JAX-RS clients *Use server-sent events to implement server-side code *Secure Java EE 8 web services with JSON Web Tokens Who this book is for If you're a Java developer who wants to learn how to implement web services using the latest Java EE 8 APIs, this book is for you. Though no prior knowledge of Java EE 8 is required, experience with a previous Java EE version will be beneficial.

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