Sql Server Machine Learning Services R
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Sql Server 2017 Machine Learning Services With R
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Author : Tomaz Kastrun
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-02-27
Sql Server 2017 Machine Learning Services With R written by Tomaz Kastrun and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-27 with Computers categories.
Develop and run efficient R scripts and predictive models for SQL Server 2017 Key Features Learn how you can combine the power of R and SQL Server 2017 to build efficient, cost-effective data science solutions Leverage the capabilities of R Services to perform advanced analytics—from data exploration to predictive modeling A quick primer with practical examples to help you get up- and- running with SQL Server 2017 Machine Learning Services with R, as part of database solutions with continuous integration / continuous delivery. Book Description R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power. What you will learn Get an overview of SQL Server 2017 Machine Learning Services with R Manage SQL Server Machine Learning Services from installation to configuration and maintenance Handle and operationalize R code Explore RevoScaleR R algorithms and create predictive models Deploy, manage, and monitor database solutions with R Extend R with SQL Server 2017 features Explore the power of R for database administrators Who this book is for This book is for data analysts, data scientists, and database administrators with some or no experience in R but who are eager to easily deliver practical data science solutions in their day-to-day work (or future projects) using SQL Server.
Sql Server Machine Learning Services R
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Author : Adam Wilbert
language : en
Publisher:
Release Date : 2020
Sql Server Machine Learning Services R written by Adam Wilbert and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
SQL Server now includes support for direct execution of R code. This integration allows complex data science analyses to be performed quickly in a secure environment, without having to export data sets first. In this course, database expert Adam Wilbert walks through the steps of enabling the required components-including Machine Learning Services for R-and writing basic R scripts. He also shows how to retrieve and work with data stored in SQL Server tables, create data visualizations with external R libraries, and package scripts as stored procedures. At the end of the course, traditional SQL Server users will be able to dive deeper into using R and traditional R developers will be able to take advantage of using SQL Server as the source of data to create higher-performing analyses.
Microsoft Sql Server 2019 A Beginner S Guide Seventh Edition
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Author : Dusan Petkovic
language : en
Publisher: McGraw Hill Professional
Release Date : 2020-01-03
Microsoft Sql Server 2019 A Beginner S Guide Seventh Edition written by Dusan Petkovic and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-03 with Computers categories.
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Get Up to Speed on Microsoft® SQL Server® 2019 Quickly and Easily Start working with Microsoft SQL Server 2019 in no time with help from this thoroughly revised, practical resource. Filled with real-world examples and hands-on exercises, Microsoft SQL Server 2019: A Beginner’s Guide, Seventh Edition starts by explaining fundamental relational database system concepts. From there, you’ll learn how to write Transact-SQL statements, execute simple and complex database queries, handle system administration and security, and use powerful analysis and reporting tools. New topics such as SQL and JSON support, graph databases, and support for machine learning with R and Python are also covered in this step-by-step tutorial. • Install, configure, and customize Microsoft SQL Server 2019 • Create and modify database objects with Transact-SQL statements • Write stored procedures and user-defined functions • Handle backup and recovery, and automate administrative tasks • Tune your database system for optimal availability and reliability • Secure your system using authentication, encryption, and authorization • Work with SQL Server Analysis Services, Reporting Services, and other BI tools • Gain knowledge of relational storage, presentation, and retrieval of data stored in the JSON format • Manage graphs using SQL Server Graph Databases • Learn about machine learning support for R and Python
Data Science With Sql Server Quick Start Guide
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Author : Dejan Sarka
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-08-31
Data Science With Sql Server Quick Start Guide written by Dejan Sarka and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-31 with Computers categories.
Get unique insights from your data by combining the power of SQL Server, R and Python Key Features Use the features of SQL Server 2017 to implement the data science project life cycle Leverage the power of R and Python to design and develop efficient data models find unique insights from your data with powerful techniques for data preprocessing and analysis Book Description SQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you. This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. It covers all stages of a data science project, from businessand data understanding,through data overview, data preparation, modeling and using algorithms, model evaluation, and deployment. You will learn to use the engines and languages that come with SQL Server, including ML Services with R and Python languages and Transact-SQL. You will also learn how to choose which algorithm to use for which task, and learn the working of each algorithm. What you will learn Use the popular programming languages,T-SQL, R, and Python, for data science Understand your data with queries and introductory statistics Create and enhance the datasets for ML Visualize and analyze data using basic and advanced graphs Explore ML using unsupervised and supervised models Deploy models in SQL Server and perform predictions Who this book is for SQL Server professionals who want to start with data science, and data scientists who would like to start using SQL Server in their projects will find this book to be useful. Prior exposure to SQL Server will be helpful.
Exam Ref 70 774 Perform Cloud Data Science With Azure Machine Learning
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Author : Ginger Grant
language : en
Publisher: Microsoft Press
Release Date : 2018-03-01
Exam Ref 70 774 Perform Cloud Data Science With Azure Machine Learning written by Ginger Grant and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-01 with Computers categories.
Prepare for Microsoft Exam 70-774–and help demonstrate your real-world mastery of performing key data science activities with Azure Machine Learning services. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: Prepare data for analysis in Azure Machine Learning and export from Azure Machine Learning Develop machine learning models Operationalize and manage Azure Machine Learning Services Use other services for machine learning This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are familiar with Azure data services, machine learning concepts, and common data science processes About the Exam Exam 70-774 focuses on skills and knowledge needed to prepare data for analysis with Azure Machine Learning; find key variables describing your data’s behavior; develop models and identify optimal algorithms; train, validate, deploy, manage, and consume Azure Machine Learning Models; and leverage related services and APIs. About Microsoft Certification Passing this exam as well as Exam 70-773: Analyzing Big Data with Microsoft R earns your MCSA: Machine Learning certifi¿cation, demonstrating your expertise in operationalizing Microsoft Azure machine learning and Big Data with R Server and SQL R Services. See full details at: microsoft.com/learning
Advanced Analytics In Power Bi With R And Python
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Author : Ryan Wade
language : en
Publisher: Apress
Release Date : 2020-09-05
Advanced Analytics In Power Bi With R And Python written by Ryan Wade and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-05 with Computers categories.
This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard to do, if not impossible, using native Power BI tools without Power BI Premium capacity. For example, you will learn to score Power BI data using custom data science models, including powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support. If you are a BI developer, business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you to do that. What You Will Learn Create advanced data visualizations through R using the ggplot2 package Ingest data using R and Python to overcome the limitations of Power Query Apply machine learning models to your data using R and Python Incorporate advanced AI in Power BI via Microsoft Cognitive Services, IBM Watson, and pre-trained models in SQL Server Machine Learning Services Perform string manipulations not otherwise possible in Power BI using R and Python Who This Book Is For Power users, data analysts, and data scientists who want to go beyond Power BI’s built-in functionality to create advanced visualizations, transform data in ways not otherwise supported, and automate data ingestion from sources such as SQL Server and Excel in a more succinct way
Machine Learning With Microsoft Technologies
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Author : Leila Etaati
language : en
Publisher: Apress
Release Date : 2019-06-12
Machine Learning With Microsoft Technologies written by Leila Etaati and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-12 with Computers categories.
Know how to do machine learning with Microsoft technologies. This book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more. The ability to analyze massive amounts of real-time data and predict future behavior of an organization is critical to its long-term success. Data science, and more specifically machine learning (ML), is today’s game changer and should be a key building block in every company’s strategy. Managing a machine learning process from business understanding, data acquisition and cleaning, modeling, and deployment in each tool is a valuable skill set. Machine Learning with Microsoft Technologies is a demo-driven book that explains how to do machine learning with Microsoft technologies. You will gain valuable insight into designing the best architecture for development, sharing, and deploying a machine learning solution. This book simplifies the process of choosing the right architecture and tools for doing machine learning based on your specific infrastructure needs and requirements. Detailed content is provided on the main algorithms for supervised and unsupervised machine learning and examples show ML practices using both R and Python languages, the main languages inside Microsoft technologies. What You'll Learn Choose the right Microsoft product for your machine learning solution Create and manage Microsoft’s tool environments for development, testing, and production of a machine learning project Implement and deploy supervised and unsupervised learning in Microsoft products Set up Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, and HD Insight to perform machine learning Set up a data science virtual machine and test-drive installed tools, such as Azure ML Workbench, Azure ML Server Developer, Anaconda Python, Jupyter Notebook, Power BI Desktop, Cognitive Services, machine learning and data analytics tools, and more Architect a machine learning solution factoring in all aspects of self service, enterprise, deployment, and sharing Who This Book Is For Data scientists, data analysts, developers, architects, and managers who want to leverage machine learning in their products, organization, and services, and make educated, cost-saving decisions about their ML architecture and tool set.
Hands On Data Science With Sql Server 2017
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Author : Marek Chmel
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-29
Hands On Data Science With Sql Server 2017 written by Marek Chmel and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-29 with Computers categories.
Find, explore, and extract big data to transform into actionable insights Key FeaturesPerform end-to-end data analysis—from exploration to visualizationReal-world examples, tasks, and interview queries to be a proficient data scientistUnderstand how SQL is used for big data processing using HiveQL and SparkSQLBook Description SQL Server is a relational database management system that enables you to cover end-to-end data science processes using various inbuilt services and features. Hands-On Data Science with SQL Server 2017 starts with an overview of data science with SQL to understand the core tasks in data science. You will learn intermediate-to-advanced level concepts to perform analytical tasks on data using SQL Server. The book has a unique approach, covering best practices, tasks, and challenges to test your abilities at the end of each chapter. You will explore the ins and outs of performing various key tasks such as data collection, cleaning, manipulation, aggregations, and filtering techniques. As you make your way through the chapters, you will turn raw data into actionable insights by wrangling and extracting data from databases using T-SQL. You will get to grips with preparing and presenting data in a meaningful way, using Power BI to reveal hidden patterns. In the concluding chapters, you will work with SQL Server integration services to transform data into a useful format and delve into advanced examples covering machine learning concepts such as predictive analytics using real-world examples. By the end of this book, you will be in a position to handle the growing amounts of data and perform everyday activities that a data science professional performs. What you will learnUnderstand what data science is and how SQL Server is used for big data processingAnalyze incoming data with SQL queries and visualizationsCreate, train, and evaluate predictive modelsMake predictions using trained models and establish regular retraining coursesIncorporate data source querying into SQL ServerEnhance built-in T-SQL capabilities using SQLCLRVisualize data with Reporting Services, Power View, and Power BITransform data with R, Python, and AzureWho this book is for Hands-On Data Science with SQL Server 2017 is intended for data scientists, data analysts, and big data professionals who want to master their skills learning SQL and its applications. This book will be helpful even for beginners who want to build their career as data science professionals using the power of SQL Server 2017. Basic familiarity with SQL language will aid with understanding the concepts covered in this book.
Business Data Science Combining Machine Learning And Economics To Optimize Automate And Accelerate Business Decisions
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Author : Matt Taddy
language : en
Publisher: McGraw Hill Professional
Release Date : 2019-08-23
Business Data Science Combining Machine Learning And Economics To Optimize Automate And Accelerate Business Decisions written by Matt Taddy and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-23 with Business & Economics categories.
Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.
Sql Server 2017 Developer S Guide
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Author : William Durkin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-03-16
Sql Server 2017 Developer S Guide written by William Durkin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-16 with Computers categories.
Build smarter and efficient database application systems for your organization with SQL Server 2017 Key Features Build database applications by using the development features of SQL Server 2017 Work with temporal tables to get information stored in a table at any time Use adaptive querying to enhance the performance of your queries Book Description Microsoft SQL Server 2017 is the next big step in the data platform history of Microsoft as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. Compared to its predecessor, SQL Server 2017 has evolved into Machine Learning with R services for statistical analysis and Python packages for analytical processing. This book prepares you for more advanced topics by starting with a quick introduction to SQL Server 2017’s new features and a recapitulation of the possibilities you may have already explored with previous versions of SQL Server. The next part introduces you to enhancements in the Transact-SQL language and new database engine capabilities and then switches to a completely new technology inside SQL Server: JSON support. We also take a look at the Stretch database, security enhancements, and temporal tables. Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Towards the end of the book, you’ll be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. You’ll also learn to integrate Python code in SQL Server and graph database implementations along with deployment options on Linux and SQL Server in containers for development and testing. By the end of this book, you will have the required information to design efficient, high-performance database applications without any hassle. What you will learn Explore the new development features introduced in SQL Server 2017 Identify opportunities for In-Memory OLTP technology Use columnstore indexes to get storage and performance improvements Exchange JSON data between applications and SQL Server Use the new security features to encrypt or mask the data Control the access to the data on the row levels Discover the potential of R and Python integration Model complex relationships with the graph databases in SQL Server 2017 Who this book is for Database developers and solution architects looking to design efficient database applications using SQL Server 2017 will find this book very useful. In addition, this book will be valuable to advanced analysis practitioners and business intelligence developers. Database consultants dealing with performance tuning will get a lot of useful information from this book as well. Some basic understanding of database concepts and T-SQL is required to get the best out of this book.