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Practical Machine Learning

You're reading from   Practical Machine Learning Learn how to build Machine Learning applications to solve real-world data analysis challenges with this Machine Learning book – packed with practical tutorials

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Product type Paperback
Published in Jan 2016
Publisher Packt
ISBN-13 9781784399689
Length 468 pages
Edition 1st Edition
Languages
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Author (1):
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Sunila Gollapudi Sunila Gollapudi
Author Profile Icon Sunila Gollapudi
Sunila Gollapudi
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Toc

Table of Contents (16) Chapters Close

Preface 1. Introduction to Machine learning FREE CHAPTER 2. Machine learning and Large-scale datasets 3. An Introduction to Hadoop's Architecture and Ecosystem 4. Machine Learning Tools, Libraries, and Frameworks 5. Decision Tree based learning 6. Instance and Kernel Methods Based Learning 7. Association Rules based learning 8. Clustering based learning 9. Bayesian learning 10. Regression based learning 11. Deep learning 12. Reinforcement learning 13. Ensemble learning 14. New generation data architectures for Machine learning Index

Machine learning process lifecycle and solution architecture

In this section, we will discuss the machine learning implementation process and solution architecture:

  1. The first step toward defining the solution architecture is defining the problem statement, which includes defining the goal, process, and assumptions.
  2. Determine what problem type is this problem classified under? Whether it is a classification, regression, or optimization problem?
  3. Choose a metric that will be used to measure the accuracy of the model.
  4. In order to ensure the model works well with the unseen data:
    1. Build the model using training data.
    2. Tweak the model using test data.
    3. Declare an accuracy based on the final version.

The following figure explains the flow and architecture of the underlying system:

Machine learning process lifecycle and solution architecture
You have been reading a chapter from
Practical Machine Learning
Published in: Jan 2016
Publisher: Packt
ISBN-13: 9781784399689
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