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Machine Learning for Developers

You're reading from   Machine Learning for Developers Uplift your regular applications with the power of statistics, analytics, and machine learning

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781786469878
Length 270 pages
Edition 1st Edition
Languages
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Authors (2):
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Md Mahmudul Hasan Md Mahmudul Hasan
Author Profile Icon Md Mahmudul Hasan
Md Mahmudul Hasan
Rodolfo Bonnin Rodolfo Bonnin
Author Profile Icon Rodolfo Bonnin
Rodolfo Bonnin
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction - Machine Learning and Statistical Science 2. The Learning Process FREE CHAPTER 3. Clustering 4. Linear and Logistic Regression 5. Neural Networks 6. Convolutional Neural Networks 7. Recurrent Neural Networks 8. Recent Models and Developments 9. Software Installation and Configuration

Dataset definition and retrieval

Once we have identified the data sources, the next task is to gather all the tuples or records as a homogeneous set. The format can be a tabular arrangement, a series of real values (such as audio or weather variables), and N-dimensional matrices (a set of images or cloud points), among other types.

The ETL process

The previous stages in the big data processing field evolved over several decades under the name of data mining, and then adopted the popular name of big data.

One of the best outcomes of these disciplines is the specification of the Extraction, Transform, Load (ETL) process.

This process starts with a mix of many data sources from business systems, then moves to a system that transforms...

You have been reading a chapter from
Machine Learning for Developers
Published in: Oct 2017
Publisher: Packt
ISBN-13: 9781786469878
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