Found inside – Page 124Hadoop 2.0 and Hortonworks Data Platform Through its Hortonworks University ... new Microsoft Analytics Platform System (formerly known as the Parallel Data ... Develop and manage effective real-time streaming solutions by leveraging the power of Microsoft Azure About This Book Analyze your data from various sources using Microsoft Azure Stream Analytics Develop, manage and automate your stream ... These services are secure, reliable, scalable, and cost efficient. About the book Azure Storage, Streaming, and Batch Analytics shows you how to build state-of-the-art data solutions with tools from the Microsoft Azure platform. Author Stephen Elston from Quantia Analytics performs the required data manipulation throughout the report, and then constructs and evaluates a regression model for a bicycle-sharing-demand dataset. After reading this book you will be familiar with Azure HDInsight and how it can be utilized to build big data solutions, including batch processing, stream analytics, interactive processing, and storing and retrieving data in an efficient ... Found insideThis third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models ... Found inside – Page 752.8.3 KNIME Analytics Platform KNIME is an open-source platform useful in enterprises ... A cloud version is available on Microsoft Azure and Amazon AWS. This book starts with an overview of the Azure Data Factory as a hybrid ETL/ELT orchestration service on Azure. The book then dives into data movement and the connectivity capability of Azure Data Factory. Found insideIntroduction to Azure ML Microsoft Azure ML is a new cloudbased machine learning platform offered as a fully managed cloud service. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. What You Will Learn Create advanced data visualizations via R using the ggplot2 package Ingest data using R and Python to overcome some limitations of Power Query Apply machine learning models to your data using R and Python without the ... Found insideCovers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks. Found insideThe 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 ... Found inside – Page 12IBM: IBM offers Watson Studio and the IBM Data Science Platform products. • Microsoft: Microsoft Azure provides a full spectrum of data and analytics ... Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. By the end of this book, you'll have developed a solid understanding of data analytics with Azure and its practical implementation. Found insideEven those who know how to create ML models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply AutoML to your data right away. Found insideLearn the techniques and math you need to start making sense of your data About This Book Enhance your knowledge of coding with data science theory for practical insight into data science and analysis More than just a math class, learn how ... This book will also benefit Data Scientists who want to use Azure for Machine Learning. Ê TABLE OF CONTENTSÊÊ 1. Ê Data and its power 2. Ê Evolution of Analytics and its Types 3. Ê Internet of Things 4. Ê AI and ML 5. Ê Why cloud 6. ... These two platforms join forces in Azure Databricks' an Apache Spark-based analytics platform designed to make the work of data analytics easier and more collaborative. Found inside – Page 30Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure Cloud services platform. Designed with the founders ofApache ... Found inside – Page 373Microsoft Azure [2] - Microsofts strong presence in the business software market ... data storage and analytic service for big-data analytics workloads that ... Learn how to utilize Microsoft SQL Server with NoSQL concepts for data science challenges. This book will help enhance your knowledge beyond data querying & processing tasks by implementing a data science pipeline. You will This book includes comprehensive coverage of how: To architect data lake analytics solutions by choosing suitable technologies available on Microsoft Azure The advent of microservices applications covering ecommerce or modern ... Found inside – Page 37Data management and curation platform The following are the five data ... Azure data analytics platforms (HDInsight, Data Lake Analytics, PowerBI, ... Found inside – Page 33Our data warehouse–only and data platform architectures offer different ways ... to files on Azure Blob Storage will be required for data scientists to do ... Found inside – Page iThis book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. Found insideThis book covers custom tailored tutorials to help you develop , maintain and troubleshoot data movement processes and environments using Azure Data Factory V2 and SQL Server Integration Services 2017 Found inside – Page 52Companies specialized on Big Data Analytics are typically offering Hadoop based ... PLATFORM. SYSTEM. AND. HDINSIGHT. Microsoft Azure cloud provides general ... This book will teach you how advanced machine learning can be performed in the cloud in a very cheap way. Author Stephen Elston from Quantia Analytics performs the required data manipulation throughout the report, and then constructs and evaluates a regression model for a bicycle-sharing-demand dataset. Found inside – Page 111... (https://www-01.ibm.com/software/data/infosphere/) is a widely used data ... analytics service for building and deploying models from the Azure data ... Found insideThis hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. 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. 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. This book will help you learn how to build a scalable end-to-end machine learning pipeline in Azure from experimentation and training to optimization and deployment. Found insideThis book is about making machine learning models and their decisions interpretable. Found insideHelps users understand the breadth of Azure services by organizing them into a reference framework they can use when crafting their own big-data analytics solution. Found inside – Page 216Using these programming languages as a foundation, user-friendly advanced data analytics software is intended for use by formally trained data science teams ... Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and ... Found insideStyle and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. Get started with Azure Synapse Analytics, Microsoft's modern data analytics platform. This book covers core components such as Synapse SQL, Synapse Spark, Synapse Pipelines, and many more, along with their architecture and implementation. Found insideThis book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. Found inside – Page 218The benefit of Azure Databricks is that it is an excellent platform for producing predictive models with data science. Zeiss, a leading manufacturer of ... The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive ... Found insidePrepare for Microsoft Exam 70-774–and help demonstrate your real-world mastery of performing key data science activities with Azure Machine Learning services. 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