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Hands-On Machine Learning on Google Cloud Platform

You're reading from   Hands-On Machine Learning on Google Cloud Platform Implementing smart and efficient analytics using Cloud ML Engine

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788393485
Length 500 pages
Edition 1st Edition
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Authors (3):
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Alexis Perrier Alexis Perrier
Author Profile Icon Alexis Perrier
Alexis Perrier
V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (18) Chapters Close

Preface 1. Introducing the Google Cloud Platform 2. Google Compute Engine FREE CHAPTER 3. Google Cloud Storage 4. Querying Your Data with BigQuery 5. Transforming Your Data 6. Essential Machine Learning 7. Google Machine Learning APIs 8. Creating ML Applications with Firebase 9. Neural Networks with TensorFlow and Keras 10. Evaluating Results with TensorBoard 11. Optimizing the Model through Hyperparameter Tuning 12. Preventing Overfitting with Regularization 13. Beyond Feedforward Networks – CNN and RNN 14. Time Series with LSTMs 15. Reinforcement Learning 16. Generative Neural Networks 17. Chatbots

Finding outliers in the data

Outliers are the values that, compared to others, are particularly extreme (a value clearly distant from the other available observations). The presence of outliers causes a hindrance because they tend to distort the results of data analysis, in particular in descriptive statistics and correlations. It is ideal to identify these outliers in the data cleaning phase itself; however, they can also be dealt with in the next step of the data analysis. Outliers can be univariate when they have an extreme value for a single variable, or multivariate when they have an unusual combination of values for a number of variables.

Outliers are the extreme values of a distribution that are characterized by being extremely high or extremely low compared to the rest of the distribution, thus representing isolated cases in respect to the rest of the distribution.

There...

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