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Hands-On Parallel Programming with C# 8 and .NET Core 3: Build solid enterprise software using task parallelism and multithreading
by Shakti TanwarEnhance your enterprise application development skills by mastering parallel programming techniques in .NET and C# Key Features Write efficient, fine-grained, and scalable parallel code with C# and .NET Core Experience how parallel programming works by building a powerful application Learn the fundamentals of multithreading by working with IIS and Kestrel Book Description In today's world, every CPU has a multi-core processor. However, unless your application has implemented parallel programming, it will fail to utilize the hardware's full processing capacity. This book will show you how to write modern software on the optimized and high-performing .NET Core 3 framework using C# 8. Hands-On Parallel Programming with C# 8 and .NET Core 3 covers how to build multithreaded, concurrent, and optimized applications that harness the power of multi-core processors. Once you've understood the fundamentals of threading and concurrency, you'll gain insights into the data structure in .NET Core that supports parallelism. The book will then help you perform asynchronous programming in C# and diagnose and debug parallel code effectively. You'll also get to grips with the new Kestrel server and understand the difference between the IIS and Kestrel operating models. Finally, you'll learn best practices such as test-driven development, and run unit tests on your parallel code. By the end of the book, you'll have developed a deep understanding of the core concepts of concurrency and asynchrony to create responsive applications that are not CPU-intensive. What you will learn Analyze and break down a problem statement for parallelism Explore the APM and EAP patterns and how to move legacy code to Task Apply reduction techniques to get aggregated results Create PLINQ queries and study the factors that impact their performance Solve concurrency problems caused by producer-consumer race conditions Discover the synchronization primitives available in .NET Core Understand how the threading model works with IIS and Kestrel Find out how you can make the most of server resources Who this book is for If you want to learn how task parallelism is used to build robust and scalable enterprise architecture, this book is for you. Whether you are a beginner to parallelism in C# or an experienced architect, you'll find this book useful to gain insights into the different threading models supported in .NET Standard and .NET Core. Prior knowledge of C# is required to understand the concepts covered in this book.
Hands-On Penetration Testing on Windows: Unleash Kali Linux, PowerShell, and Windows debugging tools for security testing and analysis
by Phil BramwellMaster the art of identifying vulnerabilities within the Windows OS and develop the desired solutions for it using Kali Linux.Key FeaturesIdentify the vulnerabilities in your system using Kali Linux 2018.02Discover the art of exploiting Windows kernel driversGet to know several bypassing techniques to gain control of your Windows environmentBook DescriptionWindows has always been the go-to platform for users around the globe to perform administration and ad hoc tasks, in settings that range from small offices to global enterprises, and this massive footprint makes securing Windows a unique challenge. This book will enable you to distinguish yourself to your clients.In this book, you'll learn advanced techniques to attack Windows environments from the indispensable toolkit that is Kali Linux. We'll work through core network hacking concepts and advanced Windows exploitation techniques, such as stack and heap overflows, precision heap spraying, and kernel exploitation, using coding principles that allow you to leverage powerful Python scripts and shellcode.We'll wrap up with post-exploitation strategies that enable you to go deeper and keep your access. Finally, we'll introduce kernel hacking fundamentals and fuzzing testing, so you can discover vulnerabilities and write custom exploits. By the end of this book, you'll be well-versed in identifying vulnerabilities within the Windows OS and developing the desired solutions for them.What you will learnGet to know advanced pen testing techniques with Kali Linux Gain an understanding of Kali Linux tools and methods from behind the scenesSee how to use Kali Linux at an advanced levelUnderstand the exploitation of Windows kernel driversUnderstand advanced Windows concepts and protections, and how to bypass them using Kali LinuxDiscover Windows exploitation techniques, such as stack and heap overflows and kernel exploitation, through coding principlesWho this book is forThis book is for penetration testers, ethical hackers, and individuals breaking into the pentesting role after demonstrating an advanced skill in boot camps. Prior experience with Windows exploitation, Kali Linux, and some Windows debugging tools is necessary
Hands-On Penetration Testing with Kali NetHunter: Spy on and protect vulnerable ecosystems using the power of Kali Linux for pentesting on the go
by Sean-Philip Oriyano Glen D. SinghConvert Android to a powerful pentesting platform.Key FeaturesGet up and running with Kali Linux NetHunter Connect your Android device and gain full control over Windows, OSX, or Linux devices Crack Wi-Fi passwords and gain access to devices connected over the same network collecting intellectual dataBook DescriptionKali NetHunter is a version of the popular and powerful Kali Linux pentesting platform, designed to be installed on mobile devices. Hands-On Penetration Testing with Kali NetHunter will teach you the components of NetHunter and how to install the software. You’ll also learn about the different tools included and how to optimize and use a package, obtain desired results, perform tests, and make your environment more secure. Starting with an introduction to Kali NetHunter, you will delve into different phases of the pentesting process. This book will show you how to build your penetration testing environment and set up your lab. You will gain insight into gathering intellectual data, exploiting vulnerable areas, and gaining control over target systems. As you progress through the book, you will explore the NetHunter tools available for exploiting wired and wireless devices. You will work through new ways to deploy existing tools designed to reduce the chances of detection. In the concluding chapters, you will discover tips and best practices for integrating security hardening into your Android ecosystem. By the end of this book, you will have learned to successfully use a mobile penetration testing device based on Kali NetHunter and Android to accomplish the same tasks you would traditionally, but in a smaller and more mobile form factor.What you will learnChoose and configure a hardware device to use Kali NetHunter Use various tools during pentests Understand NetHunter suite components Discover tips to effectively use a compact mobile platform Create your own Kali NetHunter-enabled device and configure it for optimal results Learn to scan and gather information from a target Explore hardware adapters for testing and auditing wireless networks and Bluetooth devicesWho this book is forHands-On Penetration Testing with Kali NetHunter is for pentesters, ethical hackers, and security professionals who want to learn to use Kali NetHunter for complete mobile penetration testing and are interested in venturing into the mobile domain. Some prior understanding of networking assessment and Kali Linux will be helpful.
Hands-On Penetration Testing with Python: Enhance your ethical hacking skills to build automated and intelligent systems
by Furqan KhanHands-On Penetration Testing with Python is for you if you are a developer with prior knowledge of Python, and want in-depth insight into the pentesting ecosystem. This book guides you through the advanced use of Python for cybersecurity and pentesting, helping you to better understand security loopholes within your infrastructure and cloud environments.
Hands-On Predictive Analytics with Python: Master the complete predictive analytics process, from problem definition to model deployment
by Alvaro FuentesThis book is for Python programmers who wants to learn predictive modeling and aspire to enter data science and machine learning areas. All you need is basic familiarity with linear algebra and statistical knowledge.
Hands-On Programming with R
by Garrett GrolemundLearn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them
The Hands-On Project Office: Guaranteeing ROI and On-Time Delivery
by Richard M. KesnerEconomic pressures have forced IT executives to demonstrate the immediate and calculable ROI of new technology deployments. Unfortunately, existing IT service delivery often drifts without serious thought as to how process improvements could lead to higher performance and customer satisfaction. This volume offers processes, techniques, and tools that IT managers can use to improve the delivery of IT products and services. This compendium details simple frameworks, practical tools, and proven best practices for successful IT project management. By explaining how to streamline the functions that capture and report information about IT delivery, the author clarifies roles, responsibilities, customer expectations, and performance measures, resulting in improved service and efficiency. Emphasizing the establishment of processes that result in repeatable success, the book provides quickly implementable solutions for IT personnel faced with the daily management of large, complex systems.
Hands-On Python Deep Learning for the Web: Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow
by Anubhav Singh Sayak PaulUse the power of deep learning with Python to build and deploy intelligent web applications Key Features Create next-generation intelligent web applications using Python libraries such as Flask and Django Implement deep learning algorithms and techniques for performing smart web automation Integrate neural network architectures to create powerful full-stack web applications Book Description When used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you'll cover the latest tools and technological practices that are being used to implement deep learning in web development using Python. Starting with the fundamentals of machine learning, you'll focus on DL and the basics of neural networks, including common variants such as convolutional neural networks (CNNs). You'll learn how to integrate them into websites with the frontends of different standard web tech stacks. The book then helps you gain practical experience of developing a deep learning-enabled web app using Python libraries such as Django and Flask by creating RESTful APIs for custom models. Later, you'll explore how to set up a cloud environment for deep learning-based web deployments on Google Cloud and Amazon Web Services (AWS). Next, you'll learn how to use Microsoft's intelligent Emotion API, which can detect a person's emotions through a picture of their face. You'll also get to grips with deploying real-world websites, in addition to learning how to secure websites using reCAPTCHA and Cloudflare. Finally, you'll use NLP to integrate a voice UX through Dialogflow on your web pages. By the end of this book, you'll have learned how to deploy intelligent web apps and websites with the help of effective tools and practices. What you will learn Explore deep learning models and implement them in your browser Design a smart web-based client using Django and Flask Work with different Python-based APIs for performing deep learning tasks Implement popular neural network models with TensorFlow.js Design and build deep web services on the cloud using deep learning Get familiar with the standard workflow of taking deep learning models into production Who this book is for This deep learning book is for data scientists, machine learning practitioners, and deep learning engineers who are looking to perform deep learning techniques and methodologies on the web. You will also find this book useful if you're a web developer who wants to implement smart techniques in the browser to make it more interactive. Working knowledge of the Python programming language and basic machine learning techniques will be beneficial.
Hands-On Python for Finance: A practical guide to implementing financial analysis strategies using Python
by Krish NaikLearn and implement quantitative finance using popular Python libraries like NumPy, pandas, and Keras Key Features Understand Python data structure fundamentals and work with time series data Use popular Python libraries including TensorFlow, Keras, and SciPy to deploy key concepts in quantitative finance Explore various Python programs and learn finance paradigms Book Description Python is one of the most popular languages used for quantitative finance. With this book, you'll explore the key characteristics of Python for finance, solve problems in finance, and understand risk management. The book starts with major concepts and techniques related to quantitative finance, and an introduction to some key Python libraries. Next, you'll implement time series analysis using pandas and DataFrames. The following chapters will help you gain an understanding of how to measure the diversifiable and non-diversifiable security risk of a portfolio and optimize your portfolio by implementing Markowitz Portfolio Optimization. Sections on regression analysis methodology will help you to value assets and understand the relationship between commodity prices and business stocks. In addition to this, you'll be able to forecast stock prices using Monte Carlo simulation. The book will also highlight forecast models that will show you how to determine the price of a call option by analyzing price variation. You'll also use deep learning for financial data analysis and forecasting. In the concluding chapters, you will create neural networks with TensorFlow and Keras for forecasting and prediction. By the end of this book, you will be equipped with the skills you need to perform different financial analysis tasks using Python What you will learn Clean financial data with data preprocessing Visualize financial data using histograms, color plots, and graphs Perform time series analysis with pandas for forecasting Estimate covariance and the correlation between securities and stocks Optimize your portfolio to understand risks when there is a possibility of higher returns Calculate expected returns of a stock to measure the performance of a portfolio manager Create a prediction model using recurrent neural networks (RNN) with Keras and TensorFlow Who this book is for This book is ideal for aspiring data scientists, Python developers and anyone who wants to start performing quantitative finance using Python. You can also make this beginner-level guide your first choice if you're looking to pursue a career as a financial analyst or a data analyst. Working knowledge of Python programming language is necessary.
Hands-On Python Natural Language Processing: Explore tools and techniques to analyze and process text with a view to building real-world NLP applications
by Aman Kedia Mayank RasuGet well-versed with traditional as well as modern natural language processing concepts and techniques Key Features Perform various NLP tasks to build linguistic applications using Python libraries Understand, analyze, and generate text to provide accurate results Interpret human language using various NLP concepts, methodologies, and tools Book Description Natural Language Processing (NLP) is the subfield in computational linguistics that enables computers to understand, process, and analyze text. This book caters to the unmet demand for hands-on training of NLP concepts and provides exposure to real-world applications along with a solid theoretical grounding. This book starts by introducing you to the field of NLP and its applications, along with the modern Python libraries that you'll use to build your NLP-powered apps. With the help of practical examples, you'll learn how to build reasonably sophisticated NLP applications, and cover various methodologies and challenges in deploying NLP applications in the real world. You'll cover key NLP tasks such as text classification, semantic embedding, sentiment analysis, machine translation, and developing a chatbot using machine learning and deep learning techniques. The book will also help you discover how machine learning techniques play a vital role in making your linguistic apps smart. Every chapter is accompanied by examples of real-world applications to help you build impressive NLP applications of your own. By the end of this NLP book, you'll be able to work with language data, use machine learning to identify patterns in text, and get acquainted with the advancements in NLP. What you will learn Understand how NLP powers modern applications Explore key NLP techniques to build your natural language vocabulary Transform text data into mathematical data structures and learn how to improve text mining models Discover how various neural network architectures work with natural language data Get the hang of building sophisticated text processing models using machine learning and deep learning Check out state-of-the-art architectures that have revolutionized research in the NLP domain Who this book is for This NLP Python book is for anyone looking to learn NLP's theoretical and practical aspects alike. It starts with the basics and gradually covers advanced concepts to make it easy to follow for readers with varying levels of NLP proficiency. This comprehensive guide will help you develop a thorough understanding of the NLP methodologies for building linguistic applications; however, working knowledge of Python programming language and high school level mathematics is expected.
Hands-On Q-Learning with Python: Practical Q-learning with OpenAI Gym, Keras, and TensorFlow
by Nazia HabibLeverage the power of reward-based training for your deep learning models with Python Key Features Understand Q-learning algorithms to train neural networks using Markov Decision Process (MDP) Study practical deep reinforcement learning using Q-Networks Explore state-based unsupervised learning for machine learning models Book Description Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping you get familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into modelfree Q-learning and use deep Q-networks and double deep Q-networks to solve complex problems. This book will guide you in exploring use cases such as self-driving vehicles and OpenAI Gym's CartPole problem. You will also learn how to tune and optimize Q-networks and their hyperparameters. As you progress, you will understand the reinforcement learning approach to solving real-world problems. You will also explore how to use Q-learning and related algorithms in real-world applications such as scientific research. Toward the end, you'll gain a sense of what's in store for reinforcement learning. By the end of this book, you will be equipped with the skills you need to solve reinforcement learning problems using Q-learning algorithms with OpenAI Gym, Keras, and TensorFlow. What you will learn Explore the fundamentals of reinforcement learning and the state-action-reward process Understand Markov decision processes Get well versed with libraries such as Keras, and TensorFlow Create and deploy model-free learning and deep Q-learning agents with TensorFlow, Keras, and OpenAI Gym Choose and optimize a Q-Network's learning parameters and fine-tune its performance Discover real-world applications and use cases of Q-learning Who this book is for If you are a machine learning developer, engineer, or professional who wants to delve into the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.
Hands-On Qt for Python Developers: Build cross-platform GUI applications with Python and Qt 5
by Volodymyr KirichinetsBoost UI development with ready-made widgets, controls, charts, and data visualization and create stunning 2D and 3D graphics with PyQt and PySide2.Key FeaturesBuild optimized GUI applications by implementing multiprocessing and concurrencyUnderstand embedded and mobile development with PyQt and PySideLearn to create magnificent GUI applications using Pyside2 and QtQuick/QMLBook DescriptionQt is one of the most widely used and flexible frameworks for GUI application development, allowing you to write your application once and then deploy it to multiple operating systems. This book combines the best of Python and Qt to help you develop GUI applications with Python bindings, such as PyQt and PySide, that will supercharge your Python applications.The book begins with an overview of Qt and QML. You’ll start by working with PyQt GUI elements to style your applications. Then, you will learn how to use QWidget, frames, labels, and text fields, and work with graphics. This will be followed by taking you through how elements in the application communicate with each other by understanding signals, slots, and event handlers. This book will help you to gain a better understanding of the Qt framework and the tools to resolve issues when testing, linking, debugging, and multithreading your Python GUI applications. Finally, the book will help you get to grips with embedded and mobile development using PyQt and PySide.By the end of the book, you will be able to create modern, responsive, cross-platform desktop applications with the power of Qt, Python, and QML.What you will learnExplore PyQt5 and PySide2 to create comprehensive GUI applicationsFind out how threading and multiprocessing workUnderstand how to style GUIs with PyQtGet to grips with implementing buttonsUnderstand how elements communicate with signals, slots, and event handlersExplore mobile development with PyQt and PySideWho this book is forThis book is for Python developers who want to develop GUIs and cross-platform applications that are modern, responsive, and attractive. No prior knowledge of Qt or QML is required.
Hands-On Quantum Information Processing with Python: Get up and running with information processing and computing based on quantum mechanics using Python
by Dr. Makhamisa SenekaneExplore the potential of quantum information processing and understand the state of a quantum system with this practical guideKey FeaturesGet well-versed with quantum information processing using PythonUnderstand the basics of quantum cryptography by implementing quantum key distribution protocols in PythonImplement well-known games such as the CHSH and GHZ games using quantum strategies and techniquesBook DescriptionQuantum computation is the study of a subclass of computers that exploits the laws of quantum mechanics to perform certain operations that are thought to be difficult to perform on a non-quantum computer. Hands-On Quantum Information Processing with Python begins by taking you through the essentials of quantum information processing to help you explore its potential. Next, you'll become well-versed with the fundamental property of quantum entanglement and find out how to illustrate this using the teleportation protocol. As you advance, you'll discover how quantum circuits and algorithms such as Simon's algorithm, Grover's algorithm, and Shor's algorithm work, and get to grips with quantum cryptography by implementing important quantum key distribution (QKD) protocols in Python. You will also learn how to implement non-local games such as the CHSH game and the GHZ game by using Python. Finally, you'll cover key quantum machine learning algorithms, and these implementations will give you full rein to really play with and fully understand more complicated ideas. By the end of this quantum computing book, you will have gained a deeper understanding and appreciation of quantum information.What you will learnDiscover how quantum circuits and quantum algorithms workFamiliarize yourself with non-local games and learn how to implement themGet to grips with various quantum computing modelsImplement quantum cryptographic protocols such as BB84 and B92 in PythonExplore entanglement and teleportation in quantum systemsFind out how to measure and apply operations to qubitsDelve into quantum computing with the continuous-variable quantum stateGet acquainted with essential quantum machine learning algorithmsWho this book is forThis book is for developers, programmers, or undergraduates in computer science who want to learn about the fundamentals of quantum information processing. A basic understanding of the Python programming language is required, and a good grasp of math and statistics will be useful to get the best out of this book.
Hands-on Question Answering Systems with BERT: Applications in Neural Networks and Natural Language Processing
by Navin Sabharwal Amit AgrawalGet hands-on knowledge of how BERT (Bidirectional Encoder Representations from Transformers) can be used to develop question answering (QA) systems by using natural language processing (NLP) and deep learning. The book begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. Hands-on Question Answering Systems with BERT is a good starting point for developers and data scientists who want to develop and design NLP systems using BERT. It provides step-by-step guidance for using BERT. What You Will Learn Examine the fundamentals of word embeddings Apply neural networks and BERT for various NLP tasks Develop a question-answering system from scratch Train question-answering systems for your own data Who This Book Is For AI and machine learning developers and natural language processing developers.
Hands-On Reactive Programming in Spring 5: Build cloud-ready, reactive systems with Spring 5 and Project Reactor
by Oleh Dokuka Igor LozynskyiExplore the reactive system and create efficient microservices with Spring Boot 2.1 and Spring CloudKey FeaturesUnderstand the kind of system modern businesses require with SpringGain deeper insights into reactive programming with Reactor and Spring CloudGet in-depth knowledge on asynchronous and nonblocking communication with Spring 5 WebFluxBook DescriptionThese days, businesses need a new type of system that can remain responsive at all times. This is achievable with reactive programming; however, the development of these kinds of systems is a complex task, requiring a deep understanding of the domain. In order to develop highly responsive systems, the developers of the Spring Framework came up with Project Reactor.Hands-On Reactive Programming in Spring 5 begins with the fundamentals of Spring Reactive programming. You’ll explore the endless possibilities of building efficient reactive systems with the Spring 5 Framework along with other tools such as WebFlux and Spring Boot. Further on, you’ll study reactive programming techniques and apply them to databases and cross-server communication. You will advance your skills in scaling up Spring Cloud Streams and run independent, high-performant reactive microservices.By the end of the book, you will be able to put your skills to use and get on board with the reactive revolution in Spring 5.1!What you will learnDiscover the difference between a reactive system and reactive programmingExplore the benefits of a reactive system and understand its applicationsGet to grips with using reactive programming in Spring 5Gain an understanding of Project ReactorBuild a reactive system using Spring 5 and Project ReactorCreate a highly efficient reactive microservice with Spring CloudTest, monitor, and release reactive applicationsWho this book is forThis book is for Java developers who use Spring to develop their applications and want to build robust and reactive applications that can scale in the cloud. Basic knowledge of distributed systems and asynchronous programming will help you understand the concepts covered in this book.
Hands-On Reactive Programming with Clojure: Create asynchronous, event-based, and concurrent applications, 2nd Edition
by Leonardo Borges Konrad SzydloLearn how to use RxClojure to deal with stateful computations Key Features Leverage the features of Functional Reactive Programming using Clojure Create dataflow-based systems that are the building blocks of Reactive Programming Use different Functional Reactive Programming frameworks, techniques, and patterns to solve real-world problems Book Description Reactive Programming is central to many concurrent systems, and can help make the process of developing highly concurrent, event-driven, and asynchronous applications simpler and less error-prone. This book will allow you to explore Reactive Programming in Clojure 1.9 and help you get to grips with some of its new features such as transducers, reader conditionals, additional string functions, direct linking, and socket servers. Hands-On Reactive Programming with Clojure starts by introducing you to Functional Reactive Programming (FRP) and its formulations, as well as showing you how it inspired Compositional Event Systems (CES). It then guides you in understanding Reactive Programming as well as learning how to develop your ability to work with time-varying values thanks to examples of reactive applications implemented in different frameworks. You'll also gain insight into some interesting Reactive design patterns such as the simple component, circuit breaker, request-response, and multiple-master replication. Finally, the book introduces microservices-based architecture in Clojure and closes with examples of unit testing frameworks. By the end of the book, you will have gained all the knowledge you need to create applications using different Reactive Programming approaches. What you will learn Understand how to think in terms of time-varying values and event streams Create, compose, and transform observable sequences using Reactive extensions Build a CES framework from scratch using core.async as its foundation Develop a simple ClojureScript game using Reagi Integrate Om and RxJS in a web application Implement a reactive API in Amazon Web Services (AWS) Discover helpful approaches to backpressure and error handling Get to grips with futures and their applications Who this book is for If you're interested in using Reactive Programming to build asynchronous and concurrent applications, this is the book for you. Basic knowledge of Clojure programming is necessary to understand the concepts covered in this book.
Hands-On Reactive Programming with Python: Event-driven development unraveled with RxPY
by Romain PicardA comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefitsKey FeaturesExplore the advantages of Reactive programmingUse concurrency and parallelism in RxPY to build powerful reactive applicationsDeploy and scale your reactive applications using DockerBook DescriptionReactive programming is central to many concurrent systems, but it’s famous for its steep learning curve, which makes most developers feel like they're hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various conceptsThis hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application.By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices.What you will learnStructure Python code for better readability, testing, and performanceExplore the world of event-based programmingGrasp the use of the most common operators in RxUnderstand reactive extensions beyond simple examplesMaster the art of writing reusable componentsDeploy an application on a cloud platform with Docker and TraefikWho this book is forIf you are a Python developer who wants to learn Reactive programming to build powerful concurrent and asynchronous applications, this book is for you. Basic understanding of the Python language is all you need to understand the concepts covered in this book.
Hands-On Reactive Programming with Reactor: Build reactive and scalable microservices using the Reactor framework
by Rahul SharmaDiscover how project Reactor enhances the reactive programming paradigm and allows you to build scalable asynchronous applicationsKey FeaturesUse reactive APIs, Flux, and Mono to implement reactive extensionsCreate concurrent applications without the complexity of Java's concurrent APIUnderstand techniques to implement event-driven and reactive applicationsBook DescriptionReactor is an implementation of the Java 9 Reactive Streams specification, an API for asynchronous data processing. This specification is based on a reactive programming paradigm, enabling developers to build enterprise-grade, robust applications with reduced complexity and in less time. Hands-On Reactive Programming with Reactor shows you how Reactor works, as well as how to use it to develop reactive applications in Java.The book begins with the fundamentals of Reactor and the role it plays in building effective applications. You will learn how to build fully non-blocking applications and will later be guided by the Publisher and Subscriber APIs. You will gain an understanding how to use two reactive composable APIs, Flux and Mono, which are used extensively to implement Reactive Extensions. All of these components are combined using various operations to build a complete solution. In addition to this, you will get to grips with the Flow API and understand backpressure in order to control overruns. You will also study the use of Spring WebFlux, an extension of the Reactor framework for building microservices.By the end of the book, you will have gained enough confidence to build reactive and scalable microservices.What you will learnExplore benefits of the Reactive paradigm and the Reactive Streams APIDiscover the impact of Flux and Mono implications in ReactorExpand and repeat data in stream processingGet to grips with various types of processors and choose the best oneUnderstand how to map errors to make corrections easierCreate robust tests using testing utilities offered by ReactorFind the best way to schedule the execution of codeWho this book is forIf you’re looking to develop event- and data-driven applications easily with Reactor, this book is for you. Sound knowledge of Java fundamentals is necessary to understand the concepts covered in the book.
Hands-On Recommendation Systems with Python: Start building powerful and personalized, recommendation engines with Python
by Rounak BanikWith Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the webKey FeaturesBuild industry-standard recommender systemsOnly familiarity with Python is requiredNo need to wade through complicated machine learning theory to use this bookBook DescriptionRecommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible..In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.What you will learnGet to grips with the different kinds of recommender systemsMaster data-wrangling techniques using the pandas libraryBuilding an IMDB Top 250 CloneBuild a content based engine to recommend movies based on movie metadataEmploy data-mining techniques used in building recommendersBuild industry-standard collaborative filters using powerful algorithmsBuilding Hybrid Recommenders that incorporate content based and collaborative flteringWho this book is forIf you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.
Hands-On Red Team Tactics: A practical guide to mastering Red Team operations
by Harpreet Singh Himanshu SharmaYour one-stop guide to learning and implementing Red Team tactics effectivelyKey FeaturesTarget a complex enterprise environment in a Red Team activityDetect threats and respond to them with a real-world cyber-attack simulationExplore advanced penetration testing tools and techniquesBook DescriptionRed Teaming is used to enhance security by performing simulated attacks on an organization in order to detect network and system vulnerabilities. Hands-On Red Team Tactics starts with an overview of pentesting and Red Teaming, before giving you an introduction to few of the latest pentesting tools. We will then move on to exploring Metasploit and getting to grips with Armitage. Once you have studied the fundamentals, you will learn how to use Cobalt Strike and how to set up its team server.The book introduces some common lesser known techniques for pivoting and how to pivot over SSH, before using Cobalt Strike to pivot. This comprehensive guide demonstrates advanced methods of post-exploitation using Cobalt Strike and introduces you to Command and Control (C2) servers and redirectors. All this will help you achieve persistence using beacons and data exfiltration, and will also give you the chance to run through the methodology to use Red Team activity tools such as Empire during a Red Team activity on Active Directory and Domain Controller.In addition to this, you will explore maintaining persistent access, staying untraceable, and getting reverse connections over different C2 covert channels.By the end of this book, you will have learned about advanced penetration testing tools, techniques to get reverse shells over encrypted channels, and processes for post-exploitation. What you will learnGet started with red team engagements using lesser-known methodsExplore intermediate and advanced levels of post-exploitation techniquesGet acquainted with all the tools and frameworks included in the Metasploit frameworkDiscover the art of getting stealthy access to systems via Red TeamingUnderstand the concept of redirectors to add further anonymity to your C2Get to grips with different uncommon techniques for data exfiltrationWho this book is forHands-On Red Team Tactics is for you if you are an IT professional, pentester, security consultant, or ethical hacker interested in the IT security domain and wants to go beyond Penetration Testing. Prior knowledge of penetration testing is beneficial.
Hands-On Reinforcement Learning for Games: Implementing self-learning agents in games using artificial intelligence techniques
by Micheal LanhamExplore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow Key Features Get to grips with the different reinforcement and DRL algorithms for game development Learn how to implement components such as artificial agents, map and level generation, and audio generation Gain insights into cutting-edge RL research and understand how it is similar to artificial general research Book Description With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python. Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent's productivity. As you advance, you'll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games. By the end of this book, you'll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications. What you will learn Understand how deep learning can be integrated into an RL agent Explore basic to advanced algorithms commonly used in game development Build agents that can learn and solve problems in all types of environments Train a Deep Q-Network (DQN) agent to solve the CartPole balancing problem Develop game AI agents by understanding the mechanism behind complex AI Integrate all the concepts learned into new projects or gaming agents Who this book is for If you're a game developer looking to implement AI techniques to build next-generation games from scratch, this book is for you. Machine learning and deep learning practitioners, and RL researchers who want to understand how to use self-learning agents in the game domain will also find this book useful. Knowledge of game development and Python programming experience are required.
Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
by Sudharsan RavichandiranA hands-on guide enriched with examples to master deep reinforcement learning algorithms with PythonKey FeaturesYour entry point into the world of artificial intelligence using the power of PythonAn example-rich guide to master various RL and DRL algorithmsExplore various state-of-the-art architectures along with mathBook DescriptionReinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning.By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence.What you will learnUnderstand the basics of reinforcement learning methods, algorithms, and elementsTrain an agent to walk using OpenAI Gym and TensorflowUnderstand the Markov Decision Process, Bellman’s optimality, and TD learningSolve multi-armed-bandit problems using various algorithmsMaster deep learning algorithms, such as RNN, LSTM, and CNN with applicationsBuild intelligent agents using the DRQN algorithm to play the Doom gameTeach agents to play the Lunar Lander game using DDPGTrain an agent to win a car racing game using dueling DQNWho this book is forIf you’re a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book.
Hands-On Reinforcement Learning with Python - Second Edition: Master Reinforcement And Deep Reinforcement Learning Using Openai Gym And Tensorflow
by Sudharsan RavichandiranIf you’re a machine learning developer with little or no experience with neural networks interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Basic familiarity with linear algebra, calculus, and the Python programming language is required. Some experience with TensorFlow would be a plus.
Hands-On Reinforcement Learning with R: Get up to speed with building self-learning systems using R 3.x
by Giuseppe CiaburroImplement key reinforcement learning algorithms and techniques using different R packages such as the Markov chain, MDP toolbox, contextual, and OpenAI Gym Key Features Explore the design principles of reinforcement learning and deep reinforcement learning models Use dynamic programming to solve design issues related to building a self-learning system Learn how to systematically implement reinforcement learning algorithms Book Description Reinforcement learning (RL) is an integral part of machine learning (ML), and is used to train algorithms. With this book, you'll learn how to implement reinforcement learning with R, exploring practical examples such as using tabular Q-learning to control robots. You'll begin by learning the basic RL concepts, covering the agent-environment interface, Markov Decision Processes (MDPs), and policy gradient methods. You'll then use R's libraries to develop a model based on Markov chains. You will also learn how to solve a multi-armed bandit problem using various R packages. By applying dynamic programming and Monte Carlo methods, you will also find the best policy to make predictions. As you progress, you'll use Temporal Difference (TD) learning for vehicle routing problem applications. Gradually, you'll apply the concepts you've learned to real-world problems, including fraud detection in finance, and TD learning for planning activities in the healthcare sector. You'll explore deep reinforcement learning using Keras, which uses the power of neural networks to increase RL's potential. Finally, you'll discover the scope of RL and explore the challenges in building and deploying machine learning models. By the end of this book, you'll be well-versed with RL and have the skills you need to efficiently implement it with R. What you will learn Understand how to use MDP to manage complex scenarios Solve classic reinforcement learning problems such as the multi-armed bandit model Use dynamic programming for optimal policy searching Adopt Monte Carlo methods for prediction Apply TD learning to search for the best path Use tabular Q-learning to control robots Handle environments using the OpenAI library to simulate real-world applications Develop deep Q-learning algorithms to improve model performance Who this book is for This book is for anyone who wants to learn about reinforcement learning with R from scratch. A solid understanding of R and basic knowledge of machine learning are necessary to grasp the topics covered in the book.
Hands-On RESTful API Design Patterns and Best Practices: Design, develop, and deploy highly adaptable, scalable, and secure RESTful web APIs
by Pethuru Raj Harihara SubramanianBuild effective RESTful APIs for enterprise with design patterns and REST framework's out-of-the-box capabilities Key Features Understand advanced topics such as API gateways, API securities, and cloud Implement patterns programmatically with easy-to-follow examples Modernize legacy codebase using API connectors, layers, and microservices Book Description This book deals with the Representational State Transfer (REST) paradigm, which is an architectural style that allows networked devices to communicate with each other over the internet. With the help of this book, you'll explore the concepts of service-oriented architecture (SOA), event-driven architecture (EDA), and resource-oriented architecture (ROA). This book covers why there is an insistence for high-quality APIs toward enterprise integration. It also covers how to optimize and explore endpoints for microservices with API gateways and touches upon integrated platforms and Hubs for RESTful APIs. You'll also understand how application delivery and deployments can be simplified and streamlined in the REST world. The book will help you dig deeper into the distinct contributions of RESTful services for IoT analytics and applications. Besides detailing the API design and development aspects, this book will assist you in designing and developing production-ready, testable, sustainable, and enterprise-grade APIs. By the end of the book, you'll be empowered with all that you need to create highly flexible APIs for next-generation RESTful services and applications. What you will learn Explore RESTful concepts, including URI, HATEOAS, and Code on Demand Study core patterns like Statelessness, Pagination, and Discoverability Optimize endpoints for linked microservices with API gateways Delve into API authentication, authorization, and API security implementations Work with Service Orchestration to craft composite and process-aware services Expose RESTful protocol-based APIs for cloud computing Who this book is for This book is primarily for web, mobile, and cloud services developers, architects, and consultants who want to build well-designed APIs for creating and sustaining enterprise-class applications. You'll also benefit from this book if you want to understand the finer details of RESTful APIs and their design techniques along with some tricks and tips.