You're reading from Mastering Azure Machine Learning

Product typeBook

Published inApr 2020

Reading LevelBeginner

PublisherPackt

ISBN-139781789807554

Edition1st Edition

Languages

Tools

Azure

Concepts

Machine Learning

Authors (2):

Christoph Körner

Kaijisse Waaijer

View More author details

Exploring common techniques for data preparation

After the data experimentation phase, you should have gathered enough knowledge to start preprocessing the data. This process is also often referred to as feature engineering. When coming from multiple sources, such as applications, databases, or warehouses, as well as external sources, your data cannot be analyzed or interpreted immediately.

It is, therefore, of imminent importance to preprocess data before you choose a model to interpret your problem. In addition to this, there are different steps involved in data preparation, which depend on the data that is available to you, such as the problem you want to solve, and with that, the ML algorithms that could be used for it.

You might ask yourself why data preparation is so important. The answer is that the preparation of your data might lead to improvements in model accuracy when done properly. This could be due to the relationships within your data that have been simplified...

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Mastering Azure Machine Learning

Published in: Apr 2020Publisher: PacktISBN-13: 9781789807554

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Authors (2)

Christoph Körner

Christoph Körner previously worked as a cloud solution architect for Microsoft, specializing in Azure-based big data and machine learning solutions, where he was responsible for designing end-to-end machine learning and data science platforms. He currently works for a large cloud provider on highly scalable distributed in-memory database services. Christoph has authored four books: Deep Learning in the Browser for Bleeding Edge Press, as well as Mastering Azure Machine Learning (first edition), Learning Responsive Data Visualization, and Data Visualization with D3 and AngularJS for Packt Publishing.
Read more about Christoph Körner

Kaijisse Waaijer

Kaijisse Waaijer is an experienced technologist specializing in data platforms, machine learning, and the Internet of Things. Kaijisse currently works for Microsoft EMEA as a data platform consultant specializing in data science, machine learning, and big data. She works constantly with customers across multiple industries as their trusted tech advisor, helping them optimize their organizational data to create better outcomes and business insights that drive value using Microsoft technologies. Her true passion lies within the trading systems automation and applying deep learning and neural networks to achieve advanced levels of prediction and automation.
Read more about Kaijisse Waaijer

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