LEADER 00000cam  2200313 i 4500 
001    sky303438112 
003    SKY 
005    20210607104700.0 
008    200831t20202020nyua          001 0 eng d 
020    9781484264041 
020    1484264045 
040    YDX|beng|erda|cYDX|dBDX|dJRZ|dSKYRV|dUtOrBLW 
092    006.7882|bAZU 2020 
100 1  Soh, Julian,|eauthor. 
245 10 Data science solutions on Azure :|btools and techniques 
       using databricks and MLOps /|cJulian Soh, Priyanshi Singh 
264  1 [New York] :|bApress,|c[2020] 
264  4 |c©2020 
300    xiii, 285 pages :|billustrations ;|c24 cm 
336    text|btxt|2rdacontent 
337    unmediated|bn|2rdamedia 
338    volume|bnc|2rdacarrier 
500    Includes index 
505 00 |t1. Data science in the modern enterprise --|t2. 
       Statistical techniques and concepts in data science --|t3.
       Data preparation and data engineering basics --|t4. 
       Introduction to Azure machine learning --|t5. Hands-on 
       with Azure machine learning --|t6. Apache Spark, Big Data,
       and Azure Databricks --|t7. Hands-on with Azure Databrikcs
       --|t8. Machine learning operations 
520    Understand and learn the skills needed to use modern tools
       in Microsoft Azure. This book discusses how to practically
       apply these tools in the industry, and help drive the 
       transformation of organizations into a knowledge and data-
       driven entity. It provides an end-to-end understanding of 
       data science life cycle and the techniques to efficiently 
       productionize workloads. The book starts with an 
       introduction to data science and discusses the statistical
       techniques data scientists should know. You'll then move 
       on to machine learning in Azure where you will review the 
       basics of data preparation and engineering, along with 
       Azure ML service and automated machine learning. You'll 
       also explore Azure Databricks and learn how to deploy, 
       create and manage the same. In the final chapters you'll 
       go through machine learning operations in Azure followed 
       by the practical implementation of artificial intelligence
       through machine learning. Data Science Solutions on Azure 
       will reveal how the different Azure services work together
       using real life scenarios and how-to-build solutions in a 
       single comprehensive cloud ecosystem. You will: Understand
       big data analytics with Spark in Azure Databricks ; 
       Integrate with Azure services like Azure Machine Learning 
       and Azure Synaps ; Deploy, publish and monitor your data 
       science workloads with MLOps ; Review data abstraction, 
       model management and versioning with GitHub 
650  0 Microsoft Azure (Computing platform) 
650  0 Machine learning. 
700 1  Singh, Priyanshi,|eauthor.