Hands-On Object-Oriented Programming with Kotlin. Build robust software with reusable code using OOP principles and design patterns in Kotlin

Abid Khan, Igor Kucherenko

Kotlin is an object-oriented programming language. The book is based on the latest version of Kotlin. The book provides you with a thorough understanding of programming concepts, object-oriented programming techniques, and design patterns. It includes numerous examples, explanation of concepts and keynotes. Where possible, examples and programming exercises are included. The main purpose of the book is to provide a comprehensive coverage of Kotlin features such as classes, data classes, and inheritance. It also provides a good understanding of design pattern and how Kotlin syntax works with object-oriented techniques. You will also gain familiarity with syntax in this book by writing labeled for loop and when as an expression. An introduction to the advanced concepts such as sealed classes and package level functions and coroutines is provided and we will also learn how these concepts can make the software development easy. Supported libraries for serialization, regular expression and testing are also covered in this book. By the end of the book, you would have learnt building robust and maintainable software with object oriented design patterns in Kotlin.

Hands-On One-shot Learning with Python. Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

Shruti Jadon, Ankush Garg

One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. With this book, you'll explore key approaches to one-shot learning, such as metrics-based, model-based, and optimization-based techniques, all with the help of practical examples.Hands-On One-shot Learning with Python will guide you through the exploration and design of deep learning models that can obtain information about an object from one or just a few training samples. The book begins with an overview of deep learning and one-shot learning and then introduces you to the different methods you can use to achieve it, such as deep learning architectures and probabilistic models. Once you've got to grips with the core principles, you'll explore real-world examples and implementations of one-shot learning using PyTorch 1.x on datasets such as Omniglot and MiniImageNet. Finally, you'll explore generative modeling-based methods and discover the key considerations for building systems that exhibit human-level intelligence.By the end of this book, you'll be well-versed with the different one- and few-shot learning methods and be able to use them to build your own deep learning models.

Hands-On Parallel Programming with C# 8 and .NET Core 3. Build solid enterprise software using task parallelism and multithreading

Shakti Tanwar

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.

Hands-On Penetration Testing on Windows. Unleash Kali Linux, PowerShell, and Windows debugging tools for security testing and analysis

Phil Bramwell

Windows 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.

Hands-On Penetration Testing with Kali NetHunter. Spy on and protect vulnerable ecosystems using the power of Kali Linux for pentesting on the go

Glen D. Singh, Sean-Philip Oriyano

Kali 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.

Hands-On Penetration Testing with Python. Enhance your ethical hacking skills to build automated and intelligent systems

Furqan Khan

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.

Hands-On Predictive Analytics with Python. Master the complete predictive analytics process, from problem definition to model deployment

Alvaro Fuentes

Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages.The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model.Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics.By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming.

Hands-On Python Deep Learning for the Web. Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow

Anubhav Singh, Sayak Paul

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.

Hands-On Python for DevOps. Leverage Python's native libraries to streamline your workflow and save time with automation

Ankur Roy

Python stands out as a powerhouse in DevOps, boasting unparalleled libraries and support, which makes it the preferred programming language for problem solvers worldwide. This book will help you understand the true flexibility of Python, demonstrating how it can be integrated into incredibly useful DevOps workflows and workloads, through practical examples.You'll start by understanding the symbiotic relation between Python and DevOps philosophies and then explore the applications of Python for provisioning and manipulating VMs and other cloud resources to facilitate DevOps activities. With illustrated examples, you’ll become familiar with automating DevOps tasks and learn where and how Python can be used to enhance CI/CD pipelines. Further, the book highlights Python’s role in the Infrastructure as Code (IaC) process development, including its connections with tools like Ansible, SaltStack, and Terraform. The concluding chapters cover advanced concepts such as MLOps, DataOps, and Python’s integration with generative AI, offering a glimpse into the areas of monitoring, logging, Kubernetes, and more.By the end of this book, you’ll know how to leverage Python in your DevOps-based workloads to make your life easier and save time.

Hands-On Python Natural Language Processing. Explore tools and techniques to analyze and process text with a view to building real-world NLP applications

Aman Kedia, Mayank Rasu

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.

Hands-On Q-Learning with Python. Practical Q-learning with OpenAI Gym, Keras, and TensorFlow

Nazia Habib

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 become familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into model-free 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 scientific research. Toward the end, you’ll gain insight into 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.

Hands-On Reactive Programming in Spring 5. Build cloud-ready, reactive systems with Spring 5 and Project Reactor

Oleh Dokuka, Igor Lozynskyi

These 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!

Hands-On Reactive Programming with Clojure. Create asynchronous, event-based, and concurrent applications - Second Edition

Konrad Szydlo, Leonardo Borges

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.

Hands-On Reactive Programming with Python. Event-driven development unraveled with RxPY

Romain Picard

Reactive 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.

Hands-On Reactive Programming with Reactor. Build reactive and scalable microservices using the Reactor framework

Rahul Sharma

Reactor 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.

Hands-On Recommendation Systems with Python. Start building powerful and personalized, recommendation engines with Python

Rounak Banik

Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix 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.