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You're reading from  Hands-On Data Warehousing with Azure Data Factory

Product typeBook
Published inMay 2018
PublisherPackt
ISBN-139781789137620
Edition1st Edition
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Authors (3):
Christian Cote
Christian Cote
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Christian Cote

Christian Cote is an IT professional with more than 15 years of experience working in a data warehouse, Big Data, and business intelligence projects. Christian developed expertise in data warehousing and data lakes over the years and designed many ETL/BI processes using a range of tools on multiple platforms. He's been presenting at several conferences and code camps. He currently co-leads the SQL Server PASS chapter. He is also a Microsoft Data Platform Most Valuable Professional (MVP).
Read more about Christian Cote

Michelle Gutzait
Michelle Gutzait
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Michelle Gutzait

Michelle Gutzait has been in IT for 30 years as a developer, business analyst, and database
Read more about Michelle Gutzait

Giuseppe Ciaburro
Giuseppe Ciaburro
author image
Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
Read more about Giuseppe Ciaburro

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Machine learning tasks


When we first venture into the use of artificial intelligence for data analysis, the first problem we are faced with is to choose the most appropriate algorithm for solving a specific problem. Analyzing the available algorithms, we immediately realize that the choice is not so immediate and requires an appropriate investigation.

A first approach to the problem involves the specification of the task that our machine learning algorithm will have to face. In this sense we can rest assured: there are only a handful of tasks to be analyzed even if, for each of these activities, different approaches and algorithms are available.

In fact, even if all machine learning algorithms take the same data as input, what they'll want to achieve is different. Machine learning algorithms can generally be classified into a few groups based on the tasks they were designed to solve. The typical activities in any automatic learning are as follows:

  • Regression
  • Classification
  • Clustering
  • Dimensionality...
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Hands-On Data Warehousing with Azure Data Factory
Published in: May 2018Publisher: PacktISBN-13: 9781789137620

Authors (3)

author image
Christian Cote

Christian Cote is an IT professional with more than 15 years of experience working in a data warehouse, Big Data, and business intelligence projects. Christian developed expertise in data warehousing and data lakes over the years and designed many ETL/BI processes using a range of tools on multiple platforms. He's been presenting at several conferences and code camps. He currently co-leads the SQL Server PASS chapter. He is also a Microsoft Data Platform Most Valuable Professional (MVP).
Read more about Christian Cote

author image
Michelle Gutzait

Michelle Gutzait has been in IT for 30 years as a developer, business analyst, and database
Read more about Michelle Gutzait

author image
Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
Read more about Giuseppe Ciaburro