Text Analytics with Python
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure; Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summa ...
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure; Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summa ...
Spring Persistence with Hibernate, 2nd Edition
Learn how to use the core Hibernate APIs and tools as part of the Spring Framework. This book illustrates how these two frameworks can be best utilized. Other persistence solutions available in Spring are also shown including the Java Persistence API (JPA). Spring Persistence with Hibernate, Second Edition has been updated to cover Spring Framework version 4 and Hibernate version 5. After reading and using this book, you'll have the fundamentals to apply these persistence solutions into your own mission-critical enterprise Java applications that you build using Spring. Persistence is an important set of techniques and technologies for accessing and using data, and ensuring that data is mobile regardless of specific applications and contexts. In Java development, persistence is a key factor in enterprise, e-commerce, and other transaction-oriented applications. Today, the agile and open source Spring Framework is the leading out-of-the-box, open source solution for enterprise Java ...
Learn how to use the core Hibernate APIs and tools as part of the Spring Framework. This book illustrates how these two frameworks can be best utilized. Other persistence solutions available in Spring are also shown including the Java Persistence API (JPA). Spring Persistence with Hibernate, Second Edition has been updated to cover Spring Framework version 4 and Hibernate version 5. After reading and using this book, you'll have the fundamentals to apply these persistence solutions into your own mission-critical enterprise Java applications that you build using Spring. Persistence is an important set of techniques and technologies for accessing and using data, and ensuring that data is mobile regardless of specific applications and contexts. In Java development, persistence is a key factor in enterprise, e-commerce, and other transaction-oriented applications. Today, the agile and open source Spring Framework is the leading out-of-the-box, open source solution for enterprise Java ...
Pro Angular, 2nd Edition
Get the most from Angular 2, the leading framework for building dynamic JavaScript applications. Best-selling author Adam Freeman begins by describing the MVC pattern and the benefits it can offer and then shows you how to use Angular in your projects, starting from the nuts-and-bolts and building up to the most advanced and sophisticated features, going in-depth to give you the knowledge you need. Each topic is covered clearly and concisely and is packed with the details you need to learn to be truly effective. The most important features are given a no-nonsense in-depth treatment and chapters include common problems and details of how to avoid them. ...
Get the most from Angular 2, the leading framework for building dynamic JavaScript applications. Best-selling author Adam Freeman begins by describing the MVC pattern and the benefits it can offer and then shows you how to use Angular in your projects, starting from the nuts-and-bolts and building up to the most advanced and sophisticated features, going in-depth to give you the knowledge you need. Each topic is covered clearly and concisely and is packed with the details you need to learn to be truly effective. The most important features are given a no-nonsense in-depth treatment and chapters include common problems and details of how to avoid them. ...
Mastering Machine Learning with Python in Six Steps
Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. You'll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining / analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you'll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. All the code presented in the book will be available in the form of iPython ...
Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. You'll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining / analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you'll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. All the code presented in the book will be available in the form of iPython ...
Ansible
This book is your concise guide to Ansible, the simple way to automate apps and IT infrastructure. In less than 250 pages, this book takes you from knowing nothing about configuration management to understanding how to use Ansible in a professional setting. You will learn how to create an Ansible playbook to automatically set up an environment, ready to install an open source project. You'll extract common tasks into roles that you can reuse across all your projects, and build your infrastructure on top of existing open source roles and modules that are available for you to use. You will learn to build your own modules to perform actions specific to your business. By the end you will create an entire cluster of virtualized machines, all of which have your applications and all their dependencies installed automatically. Finally, you'll test your Ansible playbooks. Ansible can do as much or as little as you want it to. Ansible: From Beginner to Pro will teach you the key skills you ...
This book is your concise guide to Ansible, the simple way to automate apps and IT infrastructure. In less than 250 pages, this book takes you from knowing nothing about configuration management to understanding how to use Ansible in a professional setting. You will learn how to create an Ansible playbook to automatically set up an environment, ready to install an open source project. You'll extract common tasks into roles that you can reuse across all your projects, and build your infrastructure on top of existing open source roles and modules that are available for you to use. You will learn to build your own modules to perform actions specific to your business. By the end you will create an entire cluster of virtualized machines, all of which have your applications and all their dependencies installed automatically. Finally, you'll test your Ansible playbooks. Ansible can do as much or as little as you want it to. Ansible: From Beginner to Pro will teach you the key skills you ...
Foundations for Analytics with Python
If you're like many of Excel's 750 million users, you want to do more with your data - like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in different formats - by using Python. After author Clinton Brownley takes you through Python basics, you'll be able to write simple scripts for processing data in spreadsheets as well as databases. You'll also learn how to use several Python modules for parsing files, grouping data, and producing statistics. No programming experience is necessary.Create and run your own Python scripts by learning basic syntax;Use Python's csv module to read and parse CSV files;Read multiple Excel worksheets and workbooks with the xlrd module;Perform database operations in MySQL or with the mysqlclient module;Create Python applications to find spe ...
If you're like many of Excel's 750 million users, you want to do more with your data - like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in different formats - by using Python. After author Clinton Brownley takes you through Python basics, you'll be able to write simple scripts for processing data in spreadsheets as well as databases. You'll also learn how to use several Python modules for parsing files, grouping data, and producing statistics. No programming experience is necessary.Create and run your own Python scripts by learning basic syntax;Use Python's csv module to read and parse CSV files;Read multiple Excel worksheets and workbooks with the xlrd module;Perform database operations in MySQL or with the mysqlclient module;Create Python applications to find spe ...
Mastering Azure Analytics
Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution. You'll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs.Understand the fundamental patterns of the data lake and lambda architecture;Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them;Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs;Understand where Azure Machine Learning fits i ...
Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution. You'll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs.Understand the fundamental patterns of the data lake and lambda architecture;Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them;Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs;Understand where Azure Machine Learning fits i ...
Making Data Visual
You have a mound of data front of you and a suite of computation tools at your disposal. Which parts of the data actually matter? Where is the insight hiding? If you're a data scientist trying to navigate the murky space between data and insight, this practical book shows you how to make sense of your data through high-level questions, well-defined data analysis tasks, and visualizations to clarify understanding and gain insights along the way. When incorporated into the process early and often, iterative visualization can help you refine the questions you ask of your data. Authors Danyel Fisher and Miriah Meyer provide detailed case studies that demonstrate how this process can evolve in the real world. You'll learn:The data counseling process for moving from general to more precise questions about your data, and arriving at a working visualization;The role that visual representations play in data discovery;Common visualization types by the tasks they f ...
You have a mound of data front of you and a suite of computation tools at your disposal. Which parts of the data actually matter? Where is the insight hiding? If you're a data scientist trying to navigate the murky space between data and insight, this practical book shows you how to make sense of your data through high-level questions, well-defined data analysis tasks, and visualizations to clarify understanding and gain insights along the way. When incorporated into the process early and often, iterative visualization can help you refine the questions you ask of your data. Authors Danyel Fisher and Miriah Meyer provide detailed case studies that demonstrate how this process can evolve in the real world. You'll learn:The data counseling process for moving from general to more precise questions about your data, and arriving at a working visualization;The role that visual representations play in data discovery;Common visualization types by the tasks they f ...
Scalable Cloud Ops with Fugue
Cloud computing represents the greatest shift in computing in more than a decade. But the promise of the cloud is unrealized. The cloud isn't just about shedding the physical data center - it's about shedding the data center mindset. Cloud infrastructure can be controlled via API calls. This means we can view it as a giant general-purpose computer - and program it. That's where the Fugue operating system and the Ludwig language come in. They automate the creation, operation, enforcement, and termination of infrastructure in the cloud. This definitive Fugue guide starts with a simple website and moves on to a more robust application with evolving infrastructure needs as you walk through the steps to harnessing the cloud. With Amazon Web Services, launch infrastructure quickly. Debug in design time. Automate deployment and enforcement of your cloud. Centralize your change control process and automate continuous auditing. Rest easy knowing configuration drift, unwanted changes, and inf ...
Cloud computing represents the greatest shift in computing in more than a decade. But the promise of the cloud is unrealized. The cloud isn't just about shedding the physical data center - it's about shedding the data center mindset. Cloud infrastructure can be controlled via API calls. This means we can view it as a giant general-purpose computer - and program it. That's where the Fugue operating system and the Ludwig language come in. They automate the creation, operation, enforcement, and termination of infrastructure in the cloud. This definitive Fugue guide starts with a simple website and moves on to a more robust application with evolving infrastructure needs as you walk through the steps to harnessing the cloud. With Amazon Web Services, launch infrastructure quickly. Debug in design time. Automate deployment and enforcement of your cloud. Centralize your change control process and automate continuous auditing. Rest easy knowing configuration drift, unwanted changes, and inf ...
Stream Processing with Apache Flink
Get started with Apache Flink, the open source framework that enables you to process streaming data - such as user interactions, sensor data, and machine logs - as it arrives. With this practical guide, you'll learn how to use Apache Flink's stream processing APIs to implement, continuously run, and maintain real-world applications. Authors Fabian Hueske, one of Flink's creators, and Vasia Kalavri, a core contributor to Flink's graph processing API (Gelly), explains the fundamental concepts of parallel stream processing and shows you how streaming analytics differs from traditional batch data analysis. Software engineers, data engineers, and system administrators will learn the basics of Flink's DataStream API, including the structure and components of a common Flink streaming application.Solve real-world problems with Apache Flink's DataStream API;Set up an environment for developing stream processing applications for Flink;Design streaming applications an ...
Get started with Apache Flink, the open source framework that enables you to process streaming data - such as user interactions, sensor data, and machine logs - as it arrives. With this practical guide, you'll learn how to use Apache Flink's stream processing APIs to implement, continuously run, and maintain real-world applications. Authors Fabian Hueske, one of Flink's creators, and Vasia Kalavri, a core contributor to Flink's graph processing API (Gelly), explains the fundamental concepts of parallel stream processing and shows you how streaming analytics differs from traditional batch data analysis. Software engineers, data engineers, and system administrators will learn the basics of Flink's DataStream API, including the structure and components of a common Flink streaming application.Solve real-world problems with Apache Flink's DataStream API;Set up an environment for developing stream processing applications for Flink;Design streaming applications an ...