Introducing Machine LearningMachine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft's powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning.
14-time Microsoft MVP Dino Esposito and Francesco Esposito help you; Explore what's known about how humans learn and how intelligent software is built; Discover which problems machine learning can address; Understand the machine learning pipeline: the steps lea ...
Fundamentals of Data VisualizationEffective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options.
This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization.
Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value; Understand the importance of redundant coding to ensure you provide key information in multiple ways; Use the book's visualizations directory, a graphica ...
MongoDB: The Definitive Guide, 3rd EditionManage your data with a system designed to support modern application development. Updated for MongoDB 4.2, the third edition of this authoritative and accessible guide shows you the advantages of using document-oriented databases. You'll learn how this secure, high-performance system enables flexible data models, high availability, and horizontal scalability.
Authors Shannon Bradshaw, Eoin Brazil, and Kristina Chodorow provide guidance for database developers, advanced configuration for system administrators, and use cases for a variety of projects. NoSQL newcomers and experienced MongoDB users will find updates on querying, indexing, aggregation, transactions, replica sets, ops management, sharding and data administration, durability, monitoring, and security.
In six parts, this book shows you how to: Work with MongoDB, perform write operations, find documents, and create complex queries; Index collections, aggregate data, and use transactions for your application; Configure a ...
Learning SQL, 3rd EditionAs data floods into your company, you need to put it to work right away—and SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps developers get up to speed with SQL fundamentals for writing database applications, performing administrative tasks, and generating reports. You'll find new chapters on SQL and big data, analytic functions, and working with very large databases.
Each chapter presents a self-contained lesson on a key SQL concept or technique using numerous illustrations and annotated examples. Exercises let you practice the skills you learn. Knowledge of SQL is a must for interacting with data. With Learning SQL, you'll quickly discover how to put the power and flexibility of this language to work.
Move quickly through SQL basics and several advanced features; Use SQL data statements to generate, manipulate, and retrieve data; Create database objects, such as tables, indexes, and constraints with SQL schema st ...
Building a Data Integration TeamFind the right people with the right skills. This book clarifies best practices for creating high-functioning data integration teams, enabling you to understand the skills and requirements, documents, and solutions for planning, designing, and monitoring both one-time migration and daily integration systems.
The growth of data is exploding. With multiple sources of information constantly arriving across enterprise systems, combining these systems into a single, cohesive, and documentable unit has become more important than ever. But the approach toward integration is much different than in other software disciplines, requiring the ability to code, collaborate, and disentangle complex business rules into a scalable model.
Data migrations and integrations can be complicated. In many cases, project teams save the actual migration for the last weekend of the project, and any issues can lead to missed deadlines or, at worst, corrupted data that needs to be reconciled post-deployment. T ...
Next-Generation Machine Learning with SparkAccess real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications.
The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry.
Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations.
Be introduced to machine learning, Spark, and Spark MLlib 2.4.x; Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries; Detect anomalies with the Isolation Forest algorithm for Spark; Use the Spark NLP and Stanford CoreNLP lib ...
Beginning Microsoft Power BIAnalyze company data quickly and easily using Microsoft's powerful data tools. Learn to build scalable and robust data models, clean and combine different data sources effectively, and create compelling and professional visuals.
Beginning Power BI is a hands-on, activity-based guide that takes you through the process of analyzing your data using the tools that that encompass the core of Microsoft's self-service BI offering. Starting with Power Query, you will learn how to get data from a variety of sources, and see just how easy it is to clean and shape the data prior to importing it into a data model. Using Power BI tabular and the Data Analysis Expressions (DAX), you will learn to create robust scalable data models which will serve as the foundation of your data analysis. From there you will enter the world of compelling interactive visualizations to analyze and gain insight into your data. You will wrap up your Power BI journey by learning how to package and share your reports an ...
Cloud Native Data Center NetworkingIf you want to study, build, or simply validate your thinking about modern cloud native data center networks, this is your book. Whether you're pursuing a multitenant private cloud, a network for running machine learning, or an enterprise data center, author Dinesh Dutt takes you through the steps necessary to design a data center that's affordable, high capacity, easy to manage, agile, and reliable.
Ideal for network architects, data center operators, and network and containerized application developers, this book mixes theory with practice to guide you through the architecture and protocols you need to create and operate a robust, scalable network infrastructure. The book offers a vendor-neutral way to look at network design. For those interested in open networking, this book is chock-full of examples using open source software, from FRR to Ansible.
In the context of a cloud native data center, you'll examine: Clos topology; Network disaggregation; Network operating system choi ...
The Practitioner's Guide to Graph DataGraph data closes the gap between the way humans and computers view the world. While computers rely on static rows and columns of data, people navigate and reason about life through relationships. This practical guide demonstrates how graph data brings these two approaches together. By working with concepts from graph theory, database schema, distributed systems, and data analysis, you'll arrive at a unique intersection known as graph thinking.
Authors Denise Koessler Gosnell and Matthias Broecheler show data engineers, data scientists, and data analysts how to solve complex problems with graph databases. You'll explore templates for building with graph technology, along with examples that demonstrate how teams think about graph data within an application.
Build an example application architecture with relational and graph technologies; Use graph technology to build a Customer 360 application, the most popular graph data pattern today; Dive into hierarchical data and troubleshoot ...
Cassandra: The Definitive Guide, 3rd EditionImagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition - updated for Cassandra 4.0 - provides the technical details and practical examples you need to put this database to work in a production environment.
Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. If you're a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra's speed and flexibility.
Understand Cassandra's distributed and decentralized structure; Use the Cassandra Query Language (CQL) and cqlsh - the CQL shell; Create a working data model and compare it with an equivalent relational model; Develop sample applications using ...