Advanced Deep Learning with R. Become an expert at designing, building, and improving advanced neural network models using R

Bharatendra Rai

Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data. Advanced Deep Learning with R will help you understand popular deep learning architectures and their variants in R, along with providing real-life examples for them. This deep learning book starts by covering the essential deep learning techniques and concepts for prediction and classification. You will learn about neural networks, deep learning architectures, and the fundamentals for implementing deep learning with R. The book will also take you through using important deep learning libraries such as Keras-R and TensorFlow-R to implement deep learning algorithms within applications. You will get up to speed with artificial neural networks, recurrent neural networks, convolutional neural networks, long short-term memory networks, and more using advanced examples. Later, you'll discover how to apply generative adversarial networks (GANs) to generate new images; autoencoder neural networks for image dimension reduction, image de-noising and image correction and transfer learning to prepare, define, train, and model a deep neural network. By the end of this book, you will be ready to implement your knowledge and newly acquired skills for applying deep learning algorithms in R through real-world examples.

Advanced Deep Learning with TensorFlow 2 and Keras. Apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more - Second Edition

Rowel Atienza

Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet), further allowing you to create your own cutting-edge AI projects.Using Keras as an open-source deep learning library, the book features hands-on projects that show you how to create more effective AI with the most up-to-date techniques.Starting with an overview of multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the book then introduces more cutting-edge techniques as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You will then learn about GANs, and how they can unlock new levels of AI performance.Next, you’ll discover how a variational autoencoder (VAE) is implemented, and how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans. You'll also learn to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.

Advanced Elasticsearch 7.0. A practical guide to designing, indexing, and querying advanced distributed search engines

Wai Tak Wong

Building enterprise-grade distributed applications and executing systematic search operations call for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and understand how you can develop a sophisticated, real-time search engine confidently. In addition to this, you'll also learn to run machine learning jobs in Elasticsearch to speed up routine tasks.You'll get started by learning to use Elasticsearch features on Hadoop and Spark and make search results faster, thereby improving the speed of query results and enhancing the customer experience. You'll then get up to speed with performing analytics by building a metrics pipeline, defining queries, and using Kibana for intuitive visualizations that help provide decision-makers with better insights. The book will later guide you through using Logstash with examples to collect, parse, and enrich logs before indexing them in Elasticsearch.By the end of this book, you will have comprehensive knowledge of advanced topics such as Apache Spark support, machine learning using Elasticsearch and scikit-learn, and real-time analytics, along with the expertise you need to increase business productivity, perform analytics, and get the very best out of Elasticsearch.

Advanced Excel 365. Master Excel 365 with practical tips and advanced AI integrations

Mercury Learning and Information, Ritu Arora

Excel is more than a spreadsheet—it's a powerhouse for data analysis, decision-making, and business productivity. This course begins with foundational concepts, such as cell referencing, formulas, and functions, before moving into tools like data validation, pivot tables, and conditional formatting. You'll also explore advanced techniques for working across multiple worksheets and creating impactful charts.The journey continues with in-depth coverage of VBA programming, where you'll learn to automate repetitive tasks, debug errors, and create user-friendly applications. Starting with the basics of macros and variables, you'll advance to building custom add-ins and employing sophisticated VBA techniques to handle complex data processes seamlessly. Each lesson combines practical examples with actionable insights.By the end of the course, you'll possess a versatile toolkit to handle everything from daily spreadsheet tasks to creating powerful custom solutions. Whether you're preparing reports, analyzing trends, or developing VBA-driven applications, this course equips you to work smarter and achieve more.

Advanced Express Web Application Development. For experienced JavaScript developers this book is all you need to build highly scalable, robust applications using Express. It takes you step by step through the development of a single page application so you learn empirically

Andrew Keig

Building an Express application that is reliable, robust, maintainable, testable, and can scale beyond a single server requires a bit of extra thought and effort. Express applications that need to survive in a production environment will need to reach out to the Node ecosystem and beyond, for support.You will start by laying the foundations of your software development journey, as you drive-out features under test. You will move on quickly to expand on your existing knowledge, learning how to create a web API and a consuming client. You will then introduce a real-time element in your application.Following on from this, you will begin a process of incrementally improving your application as you tackle security, introduce SSL support, and how to handle security vulnerabilities. Next, the book will take you through the process of scaling and then decoupling your application. Finally, you will take a look at various ways you can improve your application's performance and reliability.

Advanced Infrastructure Penetration Testing. Defend your systems from methodized and proficient attackers

Chiheb Chebbi

It has always been difficult to gain hands-on experience and a comprehensive understanding of advanced penetration testing techniques and vulnerability assessment and management. This book will be your one-stop solution to compromising complex network devices and modern operating systems. This book provides you with advanced penetration testing techniques that will help you exploit databases, web and application servers, switches or routers, Docker, VLAN, VoIP, and VPN.With this book, you will explore exploitation abilities such as offensive PowerShell tools and techniques, CI servers, database exploitation, Active Directory delegation, kernel exploits, cron jobs, VLAN hopping, and Docker breakouts. Moving on, this book will not only walk you through managing vulnerabilities, but will also teach you how to ensure endpoint protection. Toward the end of this book, you will also discover post-exploitation tips, tools, and methodologies to help your organization build an intelligent security system.By the end of this book, you will have mastered the skills and methodologies needed to breach infrastructures and provide complete endpoint protection for your system.

Advanced JavaScript. Speed up web development with the powerful features and benefits of JavaScript

Zachary Shute

If you are looking for a programming language to develop flexible and efficient applications, JavaScript is an obvious choice. Advanced JavaScript is a hands-on guide that takes you through JavaScript and its many features, one step at a time. You'll begin by learning how to use the new JavaScript syntax in ES6, and then work through the many other features that modern JavaScript has to offer. As you progress through the chapters, you’ll use asynchronous programming with callbacks and promises, handle browser events, and perform Document Object Model (DOM) manipulation. You'll also explore various methods of testing JavaScript projects. In the concluding chapters, you'll discover functional programming and learn to use it to build your apps. With this book as your guide, you'll also be able to develop APIs using Node.js and Express, create front-ends using React/Redux, and build mobile apps using React/Expo.By the end of Advanced JavaScript, you will have explored the features and benefits of JavaScript to build small applications.

Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python

Victor Marak, Nishant Shukla, John Hearty, Jeffery Yee, ...

Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data. The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce. This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering.