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Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles
by Niloy PurkaitYour one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features Design and create neural network architectures on different domains using Keras Integrate neural network models in your applications using this highly practical guide Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn Understand the fundamental nature and workflow of predictive data modeling Explore how different types of visual and linguistic signals are processed by neural networks Dive into the mathematical and statistical ideas behind how networks learn from data Design and implement various neural networks such as CNNs, LSTMs, and GANs Use different architectures to tackle cognitive tasks and embed intelligence in systems Learn how to generate synthetic data and use augmentation strategies to improve your models Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.
Hands-On Neural Networks with TensorFlow 2.0: Understand TensorFlow, from static graph to eager execution, and design neural networks
by Paolo GaleoneA comprehensive guide to developing neural network-based solutions using TensorFlow 2.0 Key Features Understand the basics of machine learning and discover the power of neural networks and deep learning Explore the structure of the TensorFlow framework and understand how to transition to TF 2.0 Solve any deep learning problem by developing neural network-based solutions using TF 2.0 Book Description TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book covers machine learning with a focus on developing neural network-based solutions. You'll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you'll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub. By the end of this TensorFlow book, you'll be ready to solve any machine learning problem by developing solutions using TF 2.0 and putting them into production. What you will learn Grasp machine learning and neural network techniques to solve challenging tasks Apply the new features of TF 2.0 to speed up development Use TensorFlow Datasets (tfds) and the tf.data API to build high-efficiency data input pipelines Perform transfer learning and fine-tuning with TensorFlow Hub Define and train networks to solve object detection and semantic segmentation problems Train Generative Adversarial Networks (GANs) to generate images and data distributions Use the SavedModel file format to put a model, or a generic computational graph, into production Who this book is for If you're a developer who wants to get started with machine learning and TensorFlow, or a data scientist interested in developing neural network solutions in TF 2.0, this book is for you. Experienced machine learning engineers who want to master the new features of the TensorFlow framework will also find this book useful. Basic knowledge of calculus and a strong understanding of Python programming will help you grasp the topics covered in this book.
Hands-On Neuroevolution with Python: Build high-performing artificial neural network architectures using neuroevolution-based algorithms
by Iaroslav OmelianenkoIncrease the performance of various neural network architectures using NEAT, HyperNEAT, ES-HyperNEAT, Novelty Search, SAFE, and deep neuroevolution Key Features Implement neuroevolution algorithms to improve the performance of neural network architectures Understand evolutionary algorithms and neuroevolution methods with real-world examples Learn essential neuroevolution concepts and how they are used in domains including games, robotics, and simulations Book Description Neuroevolution is a form of artificial intelligence learning that uses evolutionary algorithms to simplify the process of solving complex tasks in domains such as games, robotics, and the simulation of natural processes. This book will give you comprehensive insights into essential neuroevolution concepts and equip you with the skills you need to apply neuroevolution-based algorithms to solve practical, real-world problems. You'll start with learning the key neuroevolution concepts and methods by writing code with Python. You'll also get hands-on experience with popular Python libraries and cover examples of classical reinforcement learning, path planning for autonomous agents, and developing agents to autonomously play Atari games. Next, you'll learn to solve common and not-so-common challenges in natural computing using neuroevolution-based algorithms. Later, you'll understand how to apply neuroevolution strategies to existing neural network designs to improve training and inference performance. Finally, you'll gain clear insights into the topology of neural networks and how neuroevolution allows you to develop complex networks, starting with simple ones. By the end of this book, you will not only have explored existing neuroevolution-based algorithms, but also have the skills you need to apply them in your research and work assignments. What you will learn Discover the most popular neuroevolution algorithms – NEAT, HyperNEAT, and ES-HyperNEAT Explore how to implement neuroevolution-based algorithms in Python Get up to speed with advanced visualization tools to examine evolved neural network graphs Understand how to examine the results of experiments and analyze algorithm performance Delve into neuroevolution techniques to improve the performance of existing methods Apply deep neuroevolution to develop agents for playing Atari games Who this book is for This book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking to implement neuroevolution algorithms from scratch. Working knowledge of the Python programming language and basic knowledge of deep learning and neural networks are mandatory.
Hands-on Nuxt.js Web Development: Build universal and static-generated Vue.js applications using Nuxt.js
by Lau Tiam KokLearn Nuxt.js for building server-side rendered, static-generated, and production-ready Vue.js web applications with the help of practical examples Key Features Explore techniques for authentication, testing, and deployment to build your first complete Nuxt.js web app Write cleaner, maintainable, and scalable isomorphic JavaScript web applications Transform your Vue.js application into universal and static-generated web apps Book Description Nuxt.js is a progressive web framework built on top of Vue.js for server-side rendering (SSR). With Nuxt.js and Vue.js, building universal and static-generated applications from scratch is now easier than ever before. This book starts with an introduction to Nuxt.js and its constituents as a universal SSR framework. You'll learn the fundamentals of Nuxt.js and find out how you can integrate it with the latest version of Vue.js. You'll then explore the Nuxt.js directory structure and set up your first Nuxt.js project using pages, views, routing, and Vue components. With the help of practical examples, you'll learn how to connect your Nuxt.js application with the backend API by exploring your Nuxt.js application's configuration, plugins, modules, middleware, and the Vuex store. The book shows you how you can turn your Nuxt.js application into a universal or static-generated application by working with REST and GraphQL APIs over HTTP requests. Finally, you'll get to grips with security techniques using authorization, package your Nuxt.js application for testing, and deploy it to production. By the end of this web development book, you'll have developed a solid understanding of using Nuxt.js for your projects and be able to build secure, end-to-end tested, and scalable web applications with SSR, data handling, and SEO capabilities. What you will learn Integrate Nuxt.js with the latest version of Vue.js Extend your Vue.js applications using Nuxt.js pages, components, routing, middleware, plugins, and modules Create a basic real-time web application using Nuxt.js, Node.js, Koa.js and RethinkDB Develop universal and static-generated web applications with Nuxt.js, headless CMS and GraphQL Build Node.js and PHP APIs from scratch with Koa.js, PSRs, GraphQL, MongoDB and MySQL Secure your Nuxt.js applications with the JWT authentication Discover best practices for testing and deploying your Nuxt.js applications Who this book is for The book is for any JavaScript or full-stack developer who wants to build server-side rendered Vue.js apps. A basic understanding of the Vue.js framework will assist with understanding key concepts covered in the book.
Hands-On Object-Oriented Programming with C#: Build maintainable software with reusable code using C#
by Raihan TaherEnhance your programming skills by learning the intricacies of object oriented programming in C# 8Key FeaturesUnderstand the four pillars of OOP; encapsulation, inheritance, abstraction and polymorphismLeverage the latest features of C# 8 including nullable reference types and Async StreamsExplore various design patterns, principles, and best practices in OOPBook DescriptionObject-oriented programming (OOP) is a programming paradigm organized around objects rather than actions, and data rather than logic. With the latest release of C#, you can look forward to new additions that improve object-oriented programming. This book will get you up to speed with OOP in C# in an engaging and interactive way. The book starts off by introducing you to C# language essentials and explaining OOP concepts through simple programs. You will then go on to learn how to use classes, interfacesm and properties to write pure OOP code in your applications. You will broaden your understanding of OOP further as you delve into some of the advanced features of the language, such as using events, delegates, and generics. Next, you will learn the secrets of writing good code by following design patterns and design principles. You'll also understand problem statements with their solutions and learn how to work with databases with the help of ADO.NET. Further on, you'll discover a chapter dedicated to the Git version control system. As you approach the conclusion, you'll be able to work through OOP-specific interview questions and understand how to tackle them. By the end of this book, you will have a good understanding of OOP with C# and be able to take your skills to the next level.What you will learnMaster OOP paradigm fundamentals Explore various types of exceptions Utilize C# language constructs efficiently Solve complex design problems by understanding OOP Understand how to work with databases using ADO.NET Understand the power of generics in C#Get insights into the popular version control system, Git Learn how to model and design your softwareWho this book is forThis book is designed for people who are new to object-oriented programming. Basic C# skills are assumed, however, prior knowledge of OOP in any other language is not required.
Hands-On Object-Oriented Programming with Kotlin: Build robust software with reusable code using OOP principles and design patterns in Kotlin
by Igor Kucherenko Abid KhanLearn everything you need to know about object-oriented programming with the latest features of Kotlin 1.3Key FeaturesA practical guide to understand objects and classes in KotlinLearn to write asynchronous, non-blocking codes with Kotlin coroutinesExplore Encapsulation, Inheritance, Polymorphism, and Abstraction in KotlinBook DescriptionKotlin 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.What you will learnGet an overview of the Kotlin programming languageDiscover Object-oriented programming techniques in Kotlin Understand Object-oriented design patternsUncover multithreading by Kotlin wayUnderstand about arrays and collectionsUnderstand the importance of object-oriented design patternsUnderstand about exception handling and testing in OOP with KotlinWho this book is forThis book is for programmers and developers who wish to learn Object-oriented programming principles and apply them to build robust and scalable applications. Basic knowledge in Kotlin programming is assumed
Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch
by Shruti Jadon Ankush GargGet to grips with building powerful deep learning models using PyTorch and scikit-learn Key Features Learn how you can speed up the deep learning process with one-shot learning Use Python and PyTorch to build state-of-the-art one-shot learning models Explore architectures such as Siamese networks, memory-augmented neural networks, model-agnostic meta-learning, and discriminative k-shot learning Book Description 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. What you will learn Get to grips with the fundamental concepts of one- and few-shot learning Work with different deep learning architectures for one-shot learning Understand when to use one-shot and transfer learning, respectively Study the Bayesian network approach for one-shot learning Implement one-shot learning approaches based on metrics, models, and optimization in PyTorch Discover different optimization algorithms that help to improve accuracy even with smaller volumes of data Explore various one-shot learning architectures based on classification and regression Who this book is for If you're an AI researcher or a machine learning or deep learning expert looking to explore one-shot learning, this book is for you. It will help you get started with implementing various one-shot techniques to train models faster. Some Python programming experience is necessary to understand the concepts covered in this book.
Hands-On Oracle Application Express Security
by RecxAn example-driven approach to securing Oracle APEX applicationsAs a Rapid Application Development framework, Oracle Application Express (APEX) allows websites to easily be created based on data within an Oracle database. Using only a web browser, you can develop and deploy professional applications that are both fast and secure. However, as with any website, there is a security risk and threat, and securing APEX applications requires some specific knowledge of the framework. Written by well-known security specialists Recx, this book shows you the correct ways to implement your APEX applications to ensure that they are not vulnerable to attacks. Real-world examples of a variety of security vulnerabilities demonstrate attacks and show the techniques and best practices for making applications secure. Divides coverage into four sections, three of which cover the main classes of threat faced by web applications and the forth covers an APEX-specific protection mechanismAddresses the security issues that can arise, demonstrating secure application designExamines the most common class of vulnerability that allows attackers to invoke actions on behalf of other users and access sensitive dataThe lead-by-example approach featured in this critical book teaches you basic "hacker" skills in order to show you how to validate and secure your APEX applications.
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.