Видавець: Packt Publishing
Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools. As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.
609
Eлектронна книга

Recurrent Neural Networks with Python Quick Start Guide. Sequential learning and language modeling with TensorFlow

Simeon Kostadinov

Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood.After reading the book, you will be confident with the fundamentals of RNNs, and be ready to pursue further study, along with developing skills in this exciting field.

610
Eлектронна книга

VMware vSphere 6.7 Data Center Design Cookbook. Over 100 practical recipes to help you design a powerful virtual infrastructure based on vSphere 6.7 - Third Edition

Mike Brown, Hersey Cartwright

VMware is the industry leader in data center virtualization. The vSphere 6.x suite of products provides a robust and resilient platform to virtualize server and application workloads.This book uses proven infrastructure design principles and applies them to VMware vSphere 6.7 virtual data center design through short and focused recipes on each design aspect. The second edition of this book focused on vSphere 6.0. vSphere features released since then necessitate an updated design guide, which includes recipes for upgrading to 6.7, vCenter HA; operational improvements; cutting-edge, high-performance storage access such as RDMA and Pmem; security features such as encrypted vMotion and VM-level encryption; Proactive HA; HA Orchestrated Restart; Predictive DRS; and more.By the end of the book, you will be able to achieve enhanced compute, storage, network, and management capabilities for your virtual data center.

611
Eлектронна книга

Mastering Java Machine Learning. A Java developer's guide to implementing machine learning and big data architectures

Uday Kamath, Krishna Choppella

Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science.This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today.On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain.

612
Eлектронна книга

Mastering PostgreSQL 9.6. A comprehensive guide for PostgreSQL 9.6 developers and administrators

Hans-Jürgen Schönig

PostgreSQL is an open source database used for handling large datasets (Big Data) and as a JSON document database. It also has applications in the software and web domains. This book will enable you to build better PostgreSQL applications and administer databases more efficiently.We begin by explaining the advanced database design concepts in PostgreSQL 9.6, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery and high availability, and much more. You will understand the common and not-so-common troubleshooting problems and how you can overcome them.By the end of this book, you will have an expert-level command of the advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL.

613
Eлектронна книга

Hands-On Dashboard Development with QlikView. Practical guide to creating interactive and user-friendly business intelligence dashboards

Abhishek Agarwal

QlikView is one of the market leaders when it comes to building effective Business Intelligence solutions. This book will show how you can leverage its power to build your own dashboards to tell your own data story.The book starts with showing you how to connect your data to QlikView and create your own QlikView application. You will learn how to add data from multiple sources, create a data model by joining data, and then review it on the front end. You will work with QlikView components such as charts, list boxes, input boxes, and text objects to create stunning visualizations that help give actionable business insights. You will also learn how to perform analysis on your data in QlikView and master the various types of security measures to be taken in QlikView.By the end of this book, you will have all the essential knowledge required for insightful data storytelling and creating useful BI dashboards using QlikView.

614
Eлектронна книга

Java Programming for Beginners. Learn the fundamentals of programming with Java

Mark Lassoff

Java is an object-oriented programming language, and is one of the most widely accepted languages because of its design and programming features, particularly in its promise that you can write a program once and run it anywhere. Java Programming for Beginners is an excellent introduction to the world of Java programming, taking you through the basics of Java syntax and the complexities of object-oriented programming. You'll gain a full understanding of Java SE programming and will be able to write Java programs with graphical user interfaces that run on PC, Mac, or Linux machines. This book is full of informative and entertaining content, challenging exercises, and dozens of code examples you can run and learn from.By reading this book, you’ll move from understanding the data types in Java, through loops and conditionals, and on to functions, classes, and file handling. The book finishes with a look at GUI development and training on how to work with XML. The book takes an efficient route through the Java landscape, covering all of the core topics that a Java developer needs. Whether you’re an absolute beginner to programming, or a seasoned programmer approaching an object-oriented language for the first time, Java Programming for Beginners delivers the focused training you need to become a Java developer.

615
Eлектронна книга

TensorFlow Reinforcement Learning Quick Start Guide. Get up and running with training and deploying intelligent, self-learning agents using Python

Kaushik Balakrishnan

Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving.The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator.By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems.

616
Eлектронна книга

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.

617
Eлектронна книга

Information Security Handbook. Develop a threat model and incident response strategy to build a strong information security framework

Darren Death

Having an information security mechanism is one of the most crucial factors for any organization. Important assets of organization demand a proper risk management and threat model for security, and so information security concepts are gaining a lot of traction. This book starts with the concept of information security and shows you why it’s important.It then moves on to modules such as threat modeling, risk management, and mitigation. It also covers the concepts of incident response systems, information rights management, and more. Moving on, it guides you to build your own information security framework as the best fit for your organization. Toward the end, you’ll discover some best practices that can be implemented to make your security framework strong. By the end of this book, you will be well-versed with all the factors involved in information security, which will help you build a security framework that is a perfect fit your organization’s requirements.

618
Eлектронна книга

Advanced Deep Learning with Keras. Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more

Rowel Atienza

Recent developments in deep learning, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Deep Reinforcement Learning (DRL) are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like.Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, you'll find hands-on projects throughout that show you how to create more effective AI with the latest techniques.The journey begins with an overview of MLPs, CNNs, and RNNs, which are the building blocks for the more advanced techniques in the book. You’ll learn how to implement deep learning models with Keras and TensorFlow 1.x, and move forwards to advanced techniques, as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You then learn all about GANs, and how they can open new levels of AI performance. Next, you’ll get up to speed with how VAEs are implemented, and you’ll see how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans - a major stride forward for modern AI. To complete this set of advanced techniques, you'll learn how to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.

619
Eлектронна книга

Learn Arduino Prototyping in 10 days. Your crash course to build innovative devices

Kallol Bosu Roy Choudhuri

This book is a quick, 10-day crash course that will help you become well acquainted with the Arduino platform. The primary focus is to empower you to use the Arduino platform by applying basic fundamental principles. You will be able to apply these principles to build almost any type of physical device. The projects you will work through in this book are self-contained micro-controllerprojects, interfacing with single peripheral devices (such as sensors), building compound devices (multiple devices in a single setup), prototyping standalone devices (powered from independent power sources), working with actuators (such as DC motors), interfacing with an AC-powered device, wireless devices (with Infrared, Radio Frequency and GSM techniques), and finally implementing the Internet of Things (using the ESP8266 series Wi-Fi chip with an IoT cloud platform). The first half of the book focuses on fundamental techniques and building basictypes of device, and the final few chapters will show you how to prototype wirelessdevices. By the end of this book, you will have become acquainted with the fundamentalprinciples in a pragmatic and scientific manner. You will also be confident enough totake up new device prototyping challenges.

620
Eлектронна книга

AWS Lambda Quick Start Guide. Learn how to build and deploy serverless applications on AWS

Markus Klems

AWS Lambda is a part of AWS that lets you run your code without provisioning or managing servers. This enables you to deploy applications and backend services that operate with no upfront cost. This book gets you up to speed on how to build scalable systems and deploy serverless applications with AWS Lambda.The book starts with the fundamental concepts of AWS Lambda, and then teaches you how to combine your applications with other AWS services, such as AmazonAPI Gateway and DynamoDB. This book will also give a quick walk through on how to use the Serverless Framework to build larger applications that can structure code or autogenerate boilerplate code that can be used to get started quickly for increased productivity.Toward the end of the book, you will learn how to write, run, and test Lambda functions using Node.js, Java, Python, and C#.

621
Eлектронна книга

Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow - Second Edition

Sebastian Raschka, Vahid Mirjalili

Publisher's Note: This edition from 2017 is outdated and is not compatible with TensorFlow 2 or any of the most recent updates to Python libraries. A new third edition, updated for 2020 and featuring TensorFlow 2 and the latest in scikit-learn, reinforcement learning, and GANs, has now been published.Machine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka’s bestselling book, Python Machine Learning. Using Python's open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis.Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow 1.x deep learning library. The scikit-learn code has also been fully updated to v0.18.1 to include improvements and additions to this versatile machine learning library. Sebastian Raschka and Vahid Mirjalili’s unique insight and expertise introduce you to machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. By the end of the book, you’ll be ready to meet the new data analysis opportunities.If you’ve read the first edition of this book, you’ll be delighted to find a balance of classical ideas and modern insights into machine learning. Every chapter has been critically updated, and there are new chapters on key technologies. You’ll be able to learn and work with TensorFlow 1.x more deeply than ever before, and get essential coverage of the Keras neural network library, along with updates to scikit-learn 0.18.1.

622
Eлектронна книга

SAP Business Intelligence Quick Start Guide. Actionable business insights from the SAP BusinessObjects BI platform

Vinay Singh

The SAP BusinessObjects Business Intelligence platform is a powerful reporting and analysis tool. This book is the ideal introduction to the SAP BusinessObjects Business Intelligence platform, introducing you to its data visualization, visual analytics, reporting, and dashboarding capabilities.The book starts with an overview of the BI platform and various data sources for reporting. Then, we move on to looking at data visualization, analysis, reporting, and analytics using BusinessObjects Business Intelligence tools. You will learn about the features associated with reporting, scheduling, and distribution and learn how to deploy the platform. Toward the end, you will learn about the strategies and factors that should be considered during deployment.By the end, you will be confident working with the SAP BusinessObjects Business Intelligence platform to deliver better insights for more effective decision making.

623
Eлектронна книга

Learn Chart.js. Create interactive visualizations for the Web with Chart.js 2

Helder da Rocha

Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice.This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart’s default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript.By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js.

624
Eлектронна книга

Mastering Xamarin UI Development. Build robust and a maintainable cross-platform mobile UI with Xamarin and C# 7 - Second Edition

Steven F. Daniel

This book will provide you with the knowledge and practical skills that are required to develop real-world Xamarin and Xamarin.Forms applications. You’ll learn how to create native Android app that will interact with the device camera and photo gallery, and then create a native iOS sliding tiles game. You will learn how to implement complex UI layouts and create customizable control elements based on the platform, using XAML and C# 7 code to interact with control elements within your XAML ContentPages.You’ll learn how to add location-based features by to your apps by creating a LocationService class and using the Xam.Plugin.Geolocator cross-platform library, that will be used to obtain the current device location. Next, you’ll learn how to work with and implement animations and visual effects within your UI using the PlatformEffects API, using C# code.At the end of this book, you’ll learn how to integrate Microsoft Azure App Services and use the Twitter APIs within your app. You will work with the Razor Templating Engine to build a book library HTML5 solution that will use a SQLite.net library to store, update, retrieve, and delete information within a local SQLite database. Finally, you will learn how to write unit tests using the NUnit and UITest frameworks.