Machine Learning with Microsoft Technologies Selecting the Right Architecture and Tools for Your Project /

• Κύριος συγγραφέας: Etaati, Leila (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berkeley, CA : Apress : Imprint: Apress, 2019.
• Έκδοση: 1st ed. 2019.
• Θέματα: Microsoft software.; Microsoft .NET Framework.; Artificial intelligence.; Python (Computer program language).; Microsoft and .NET.; Artificial Intelligence.; Python.

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-t...

Πίνακας περιεχομένων:

• Part I: Getting Started
• Chapter 1: Introduction to Machine Learning
• Chapter 2: Introduction to R
• Chapter 3: Introduction to Python
• Chapter 4: R Visualization in Power BI
• Part II: Machine Learning in R and Power BI
• Chapter 5: Business Understanding
• Chapter 6: Data Wrangling for Predictive Analysis
• Chapter 7: Predictive Analysis in Power Query with R
• Chapter 8: Descriptive Analysis in Power Query with R
• Part III: Machine Learning SQL Server
• Chapter 9: Using R with SQL Server 2016 and 2017
• Chapter 10: Azure Databricks
• Part IV: Machine Learning in Azure
• Chapter 11: R in Azure Data Lake
• Chapter 12: Azure Machine Learning Studio
• Chapter 13: Machine Learning in Azure Stream Analytics
• Chapter 14: Azure Machine Learning (ML) Workbench
• Chapter 15: Machine Learning on HDInsight
• Chapter 16: Data Science Virtual Machine and AI Framework
• Chapter 17: Deep Learning Tools with Cognitive Toolkit (CNTK)
• Part V: Data Science Virtual Machine
• Chapter 18: Cognitive Service Toolkit
• Chapter 19: Bot Framework
• Chapter 20: Overview on Microsoft Machine Learning Tools.