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Native Docker Clustering with Swarm. Create and manage clusters of any size
Fabrizio Soppelsa, Chanwit Kaewkasi
Docker Swarm serves as one of the crucial components of the Docker ecosystem and offers a native solution for you to orchestrate containers. It’s turning out to be one of the preferred choices for Docker clustering thanks to its recent improvements. This book covers Swarm, Swarm Mode, and SwarmKit. It gives you a guided tour on how Swarm works and how to work with Swarm. It describes how to set up local test installations and then moves to huge distributed infrastructures. You will be shown how Swarm works internally, what’s new in Swarmkit, how to automate big Swarm deployments, and how to configure and operate a Swarm cluster on the public and private cloud. This book will teach you how to meet the challenge of deploying massive production-ready applications and a huge number of containers on Swarm. You'll also cover advanced topics that include volumes, scheduling, a Libnetwork deep dive, security, and platform scalability.
Bhargav Srinivasa-Desikan
Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data.This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy.You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning.This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis.
Mercury Learning and Information, Oswald Campesato
This book introduces developers to basic concepts in NLP and machine learning, providing numerous code samples to support the topics covered. The journey begins with introductory material on NumPy and Pandas, essential for data manipulation. Following this, chapters delve into NLP concepts, algorithms, and toolkits, providing a solid foundation in natural language processing.As you progress, the book covers machine learning fundamentals and classifiers, demonstrating how these techniques are applied in NLP. Practical examples using TF2 and Keras illustrate how to implement various NLP tasks. Advanced topics include the Transformer architecture, BERT-based models, and the GPT family of models, showcasing the latest advancements in the field.The final chapters and appendices offer a comprehensive overview of related topics, including data and statistics, Python3, regular expressions, and data visualization with Matplotlib and Seaborn. Companion files with source code and figures ensure a hands-on learning experience. This book equips you with the knowledge and tools needed to excel in NLP and machine learning.
Mercury Learning and Information, Oswald Campesato
This book is for developers seeking an overview of basic concepts in Natural Language Processing (NLP). It caters to those with varied technical backgrounds, offering numerous code samples and listings to illustrate the wide range of topics covered. The journey begins with managing data relevant to NLP, followed by two chapters on fundamental NLP concepts. This foundation is reinforced with Python code samples that bring these concepts to life.The book then delves into practical NLP applications, such as sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and chatbots. These examples provide real-world context and demonstrate how NLP techniques can be applied to solve common problems. The final chapter introduces advanced topics, including the Transformer architecture, BERT-based models, and the GPT family, highlighting the latest state-of-the-art developments in the field.Appendices offer additional resources, including Python code samples on regular expressions and probability/statistical concepts, ensuring a well-rounded understanding. Companion files with source code and figures enhance the learning experience, making this book a comprehensive guide for mastering NLP techniques and applications.
Natural Language Processing: Python and NLTK. Click here to enter text
Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti...
Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it’s becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy.The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python.This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products:? NTLK essentials by Nitin Hardeniya? Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins? Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur
Mercury Learning and Information, Oswald Campesato
This book is for developers seeking an overview of basic concepts in Natural Language Processing (NLP). It caters to a technical audience, offering numerous code samples and listings to illustrate the wide range of topics covered. The journey begins with managing data relevant to NLP, followed by two chapters on fundamental NLP concepts. This foundation is reinforced with Python code samples that bring these concepts to life.The book then delves into practical NLP applications, such as sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and chatbots. These examples provide real-world context and demonstrate how NLP techniques can be applied to solve common problems. The final chapter introduces advanced topics, including the Transformer architecture, BERT-based models, and the GPT family, highlighting the latest state-of-the-art developments in the field.Appendices offer additional resources, including Python code samples on regular expressions and probability/statistical concepts, ensuring a well-rounded understanding. Companion files with source code and figures enhance the learning experience, making this book a comprehensive guide for mastering NLP techniques and applications.
Nirant Kasliwal
NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a work?ow for building NLP applications.We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn.We conclude by deploying these models as REST APIs with Flask.By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges.
Thushan Ganegedara
Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks.Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator.After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks.
Neo4j Graph Data Modeling. Design efficient and flexible databases by optimizing the power of Neo4j
Mahesh Lal, Mahesh K Lal
Sudipta Mukherjee
Generics were added as part of .NET Framework 2.0 in November 2005. Although similar to generics in Java, .NET generics do not apply type erasure but every object has unique representation at run-time. There is no performance hit from runtime casts and boxing conversions, which are normally expensive..NET offers type-safe versions of every classical data structure and some hybrid ones.This book will show you everything you need to start writing type-safe applications using generic data structures available in Generics API. You will also see how you can use several collections for each task you perform. This book is full of practical examples, interesting applications, and comparisons between Generics and more traditional approaches. Finally, each container is bench marked on the basis of performance for a given task, so you know which one to use and when.This book first covers the fundamental concepts such as type safety, Generic Methods, and Generic Containers. As the book progresses, you will learn how to join several generic containers to achieve your goals and query them efficiently using Linq. There are short exercises in every chapter to boost your knowledge.The book also teaches you some best practices, and several patterns that are commonly available in generic code.Some important generic algorithm definitions are present in Power Collection (an API created by Wintellect Inc.) that are missing from .NET framework. This book shows you how to use such algorithms seamlessly with other generic containers.The book also discusses C5 collections. Java Programmers will find themselves at home with this API. This is the closest to JCF. Some very interesting problems are solved using generic containers from .NET framework, C5, and PowerCollection Algorithms ñ a clone of Google Set and Gender Genie for example!The author has also created a website (https://www.consulttoday.com/genguide) for the book where you can find many useful tools, code snippets, and, applications, which are not the part of code-download section
Neha Shrivastava, Rishabh Verma
With the rise in the number of tools and technologies available today, developers and architects are always exploring ways to create better and smarter solutions. Before, the differences between target platforms was a major roadblock, but that's not the case now. .NET Core 2.0 By Example will take you on an exciting journey to building better software.This book provides fresh and relevant content to .NET Core 2.0 in a succinct format that’s enjoyable to read. It also delivers concepts, along with the implications, design decisions, and potential pitfalls you might face when targeting Linux and Windows systems, in a logical and simple way.With the .NET framework at its center, the book comprises of five varied projects: a multiplayer Tic-tac-toe game; a real-time chat application, Let'sChat; a chatbot; a microservice-based buying-selling application; and a movie booking application. You will start each chapter with a high-level overview of the content, followed by the above example applications described in detail. By the end of each chapter, you will not only be proficient with the concepts, but you’ll also have created a tangible component in the application.By the end of the book, you will have built five solid projects using all the tools and support provided by the .NET Core 2.0 framework.
Neha Shrivastava, Rishabh Verma
With the rise in the number of tools and technologies available today, developers and architects are always exploring ways to create better and smarter solutions. Before, the differences between target platforms was a major roadblock, but that's not the case now. .NET Core 2.0 By Example will take you on an exciting journey to building better software.This book provides fresh and relevant content to .NET Core 2.0 in a succinct format that’s enjoyable to read. It also delivers concepts, along with the implications, design decisions, and potential pitfalls you might face when targeting Linux and Windows systems, in a logical and simple way.With the .NET framework at its center, the book comprises of five varied projects: a multiplayer Tic-tac-toe game; a real-time chat application, Let'sChat; a chatbot; a microservice-based buying-selling application; and a movie booking application. You will start each chapter with a high-level overview of the content, followed by the above example applications described in detail. By the end of each chapter, you will not only be proficient with the concepts, but you’ll also have created a tangible component in the application.By the end of the book, you will have built five solid projects using all the tools and support provided by the .NET Core 2.0 framework.
Alexander Russkov
Think about how much time you usually spend building an app in a technology you're still mastering—grasping new concepts, navigating roadblocks, and even rewriting entire modules as you learn. This book saves you that time, helping you create a modern .NET MAUI application like a pro.The chapters address a wide range of tasks and concepts essential for real-world apps, including UI best practices and advanced tips, MVVM, dependency injection, performance, and memory profiling. Since real-world applications often go beyond frontend development, this book also explores integration with backend services for authentication, data processing, synchronization, and real-time updates. Additionally, you’ll learn to implement multiple AI integration strategies, all without any prior machine learning experience.Mastery comes with practice, so the book is organized with step-by-step recipes, each tackling a specific task. Each recipe includes detailed explanations to help you apply what you're learning to your own unique projects.By the end of this book, you'll have developed the skills to build high-performance, interactive cross-platform applications with .NET MAUI, saving valuable time on your future projects.
Roger Ye
An evolution of Xamarin.Forms, .NET MAUI is a cross-platform framework for creating native mobile and desktop apps with C# and XAML. Using .NET MAUI, you can develop apps that’ll run on Android, iOS, macOS, and Windows from a single shared codebase. In this revised edition of .NET MAUI Cross-Platform Application Development you will be introduced to .NET 8 and get up to speed with app development in no time.The book begins by showing you how to develop a cross-platform application using .NET MAUI, including guidance for migrating from Xamarin.Forms. You’ll gain all the knowledge needed to create a cross-platform application for Android, iOS, macOS, and Windows following an example project step by step.As you advance, you’ll integrate the latest frontend technology into your app using Blazor components, including the new Blazor Bindings feature. After this, you’ll learn how to test and deploy your apps. With new coverage on creating mock .NET MAUI components, you can develop unit tests for your application. You will additionally learn how to perform Razor component testing using bUnit.By the end of this book, you’ll have learned how to develop your own cross-platform applications using .NET MAUI.
Anthony Bickof
NetSuite ERP is a complete, scalable cloud ERP solution targeted at fast-growing, mid-sized businesses and large enterprises. It's the smartly executed combination of financial management operations and built-in business intelligence, which enables companies to make data-driven and well-informed decisions. This book will help administrators become expert enough to be seen as the NetSuite leader at their company and to be able to advise department heads on specific processes, and strategic decisions. We start with an overview of ERP and NetSuite ERP, before going on to explain the built-in features to show the breadth of NetSuite ERP's product and its ease of use. We then discuss business aspects, focusing on the most important processes in NetSuite. Then you'll understand the implementation aspects that are generic enough to cover all the features. The focus then shifts to specific skills that you will need to administer for any system, such as roles, permissions, customization, and data imports. Moving on, you'll learn how to centralize the creation of search templates and give users the tools to pivot the data and expose it to the user in useful ways, such as on the dashboard. The book ends with checklists providing actionable steps that you as an administrator can take to do your job and support the application through new releases and troubleshooting problems.
Anthony Bickof
NetSuite ERP is a complete, scalable cloud ERP solution targeted at fast-growing, mid-sized businesses and large enterprises. It's the smartly executed combination of financial management operations and built-in business intelligence, which enables companies to make data-driven and well-informed decisions. This book will help administrators become expert enough to be seen as the NetSuite leader at their company and to be able to advise department heads on specific processes, and strategic decisions. We start with an overview of ERP and NetSuite ERP, before going on to explain the built-in features to show the breadth of NetSuite ERP's product and its ease of use. We then discuss business aspects, focusing on the most important processes in NetSuite. Then you'll understand the implementation aspects that are generic enough to cover all the features. The focus then shifts to specific skills that you will need to administer for any system, such as roles, permissions, customization, and data imports. Moving on, you'll learn how to centralize the creation of search templates and give users the tools to pivot the data and expose it to the user in useful ways, such as on the dashboard. The book ends with checklists providing actionable steps that you as an administrator can take to do your job and support the application through new releases and troubleshooting problems.