Natural Language Processing with Python and spaCy
Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You'll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You'll even learn how to transform statements into questions to keep a conversation going. You'll also learn how to: Work with word vectors to mathematically find words with similar meanings; Identify patterns within data using spaCy's built-in displaCy visualizer; Automatically extract keywords from user input and store them in a relational database; Deploy a chatbot app to interact with users over the internet. ...
Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You'll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You'll even learn how to transform statements into questions to keep a conversation going. You'll also learn how to: Work with word vectors to mathematically find words with similar meanings; Identify patterns within data using spaCy's built-in displaCy visualizer; Automatically extract keywords from user input and store them in a relational database; Deploy a chatbot app to interact with users over the internet. ...
React and React Native, 3rd Edition
React and React Native, Facebook's innovative User Interface (UI) libraries, are designed to help you build robust cross-platform web and mobile applications. This updated third edition is improved and updated to cover the latest version of React. The book particularly focuses on the latest developments in the React ecosystem, such as modern Hook implementations, code splitting using lazy components and Suspense, user interface framework components using Material-UI, and Apollo. In terms of React Native, the book has been updated to version 0.62 and demonstrates how to apply native UI components for your existing mobile apps using NativeBase. You will begin by learning about the essential building blocks of React components. Next, you'll progress to working with higher-level functionalities in application development, before putting this knowledge to use by developing user interface components for the web and for native platforms. In the concluding chapters, you'll learn how to brin ...
React and React Native, Facebook's innovative User Interface (UI) libraries, are designed to help you build robust cross-platform web and mobile applications. This updated third edition is improved and updated to cover the latest version of React. The book particularly focuses on the latest developments in the React ecosystem, such as modern Hook implementations, code splitting using lazy components and Suspense, user interface framework components using Material-UI, and Apollo. In terms of React Native, the book has been updated to version 0.62 and demonstrates how to apply native UI components for your existing mobile apps using NativeBase. You will begin by learning about the essential building blocks of React components. Next, you'll progress to working with higher-level functionalities in application development, before putting this knowledge to use by developing user interface components for the web and for native platforms. In the concluding chapters, you'll learn how to brin ...
Mastering Azure Machine Learning
The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure ML and takes you through the process of data experimentation, data preparation, and feature engineering using Azure ML and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure AutoML and HyperDrive, and perform distributed training on Azure ML ...
The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure ML and takes you through the process of data experimentation, data preparation, and feature engineering using Azure ML and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure AutoML and HyperDrive, and perform distributed training on Azure ML ...
Mastering Windows Presentation Foundation, 2nd Edition
Microsoft Windows Presentation Foundation (WPF) provides several libraries and APIs for developers to create engaging user experiences. This book features a wide range of simple through to complex examples to demonstrate how to develop enterprise-grade applications for Windows desktop with WPF. This updated second edition of Mastering Windows Presentation Foundation starts by covering the benefits of using the Model-View-ViewModel (MVVM) software architectural pattern with WPF, before guiding you through debugging your WPF apps. The book will then take you through the application architecture and building the foundation layer for your apps. As you advance, you'll get to grips with data binding, explore the various built-in WPF controls, and customize them to suit your requirements. You'll learn how to create custom controls to meet your needs when the built-in functionality is not enough. You'll also learn how to enhance your applications using practical animations, stunning visuals ...
Microsoft Windows Presentation Foundation (WPF) provides several libraries and APIs for developers to create engaging user experiences. This book features a wide range of simple through to complex examples to demonstrate how to develop enterprise-grade applications for Windows desktop with WPF. This updated second edition of Mastering Windows Presentation Foundation starts by covering the benefits of using the Model-View-ViewModel (MVVM) software architectural pattern with WPF, before guiding you through debugging your WPF apps. The book will then take you through the application architecture and building the foundation layer for your apps. As you advance, you'll get to grips with data binding, explore the various built-in WPF controls, and customize them to suit your requirements. You'll learn how to create custom controls to meet your needs when the built-in functionality is not enough. You'll also learn how to enhance your applications using practical animations, stunning visuals ...
Succeeding with AI
Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It's filled with practical techniques for running data science programs that ensure they're cost effective and focused on the right business goals. Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren't enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you'll get the results you want. Succeeding with AI sets out a framework for pl ...
Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It's filled with practical techniques for running data science programs that ensure they're cost effective and focused on the right business goals. Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren't enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you'll get the results you want. Succeeding with AI sets out a framework for pl ...
Mastering Large Datasets with Python
Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project. Programming techniques that work well on laptop-sized data can slow to a crawl - or fail altogether - when applied to massive files or distributed datasets. By mastering the powerful map and reduce paradigm, along with the Python-based tools that support it, you can write data-centric applications that scale efficiently without requiring codebase rewrites as your requirements change. Ma ...
Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project. Programming techniques that work well on laptop-sized data can slow to a crawl - or fail altogether - when applied to massive files or distributed datasets. By mastering the powerful map and reduce paradigm, along with the Python-based tools that support it, you can write data-centric applications that scale efficiently without requiring codebase rewrites as your requirements change. Ma ...
Machine Learning with R, the tidyverse, and mlr
Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making recommendations or fraud detection and make predictions for sales trends, risk analysis, and other forecasts. Once the domain of academic data scientists, machine learning has become a mainstream business process, and tools like the easy-to-learn R programming language put high-quality data analysis in the hands of any programmer. Machine Learning with R, the tidyverse, and mlr teaches you widely used ML techniques and how to apply them to your own datasets using the R programming language and its powerful ecosystem of tools. This book will get you started! Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML tec ...
Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making recommendations or fraud detection and make predictions for sales trends, risk analysis, and other forecasts. Once the domain of academic data scientists, machine learning has become a mainstream business process, and tools like the easy-to-learn R programming language put high-quality data analysis in the hands of any programmer. Machine Learning with R, the tidyverse, and mlr teaches you widely used ML techniques and how to apply them to your own datasets using the R programming language and its powerful ecosystem of tools. This book will get you started! Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML tec ...
Deep Reinforcement Learning in Action
Humans learn best from feedback - we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you'll need to implement it into your own projects. Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and ...
Humans learn best from feedback - we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you'll need to implement it into your own projects. Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and ...
Spark in Action, 2nd Edition
The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, 2nd Edition, you'll learn to take advantage of Spark's core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark's powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. Analyzing enterprise data starts by reading, filtering, and merging files and streams from many sources. The Spark data processing engine handles this varied volume like a champ, delivering speeds 100 times faster than Hadoop systems. Thanks to SQL support, an intuitive interface, and a straightforward multilanguage API, you can use Spark without learning a complex new ecosystem. Spark in Action, 2nd Edition, teaches you to create end-to-end analytics ...
The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, 2nd Edition, you'll learn to take advantage of Spark's core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark's powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. Analyzing enterprise data starts by reading, filtering, and merging files and streams from many sources. The Spark data processing engine handles this varied volume like a champ, delivering speeds 100 times faster than Hadoop systems. Thanks to SQL support, an intuitive interface, and a straightforward multilanguage API, you can use Spark without learning a complex new ecosystem. Spark in Action, 2nd Edition, teaches you to create end-to-end analytics ...
RavenDB in Action
The data you encounter in the real world is usually easier to think of as objects or documents than as the tables and rows required by a standard RDBMS. RavenDB, a modern document-oriented database written in .NET, requires no schema to be declared and enables developers to work with data more naturally. RavenDB applications are high-performance, low-latency, and easy to scale and maintain. RavenDB in Action introduces RavenDB and the document database model. After explaining the basics and offering a quick-and-dirty sample application, this end-to-end guide dives into core RavenDB techniques. You'll find thoroughly-documented examples on extending RavenDB, deployment stories, and tips to ensure production readiness, along with coverage of advanced topics like full-text search. After reading this book, you should be comfortable building efficient database-backed applications using RavenDB. ...
The data you encounter in the real world is usually easier to think of as objects or documents than as the tables and rows required by a standard RDBMS. RavenDB, a modern document-oriented database written in .NET, requires no schema to be declared and enables developers to work with data more naturally. RavenDB applications are high-performance, low-latency, and easy to scale and maintain. RavenDB in Action introduces RavenDB and the document database model. After explaining the basics and offering a quick-and-dirty sample application, this end-to-end guide dives into core RavenDB techniques. You'll find thoroughly-documented examples on extending RavenDB, deployment stories, and tips to ensure production readiness, along with coverage of advanced topics like full-text search. After reading this book, you should be comfortable building efficient database-backed applications using RavenDB. ...