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R Machine Learning Projects

You're reading from   R Machine Learning Projects Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789807943
Length 334 pages
Edition 1st Edition
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Author (1):
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Dr. Sunil Kumar Chinnamgari Dr. Sunil Kumar Chinnamgari
Author Profile Icon Dr. Sunil Kumar Chinnamgari
Dr. Sunil Kumar Chinnamgari
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Table of Contents (12) Chapters Close

Preface 1. Exploring the Machine Learning Landscape FREE CHAPTER 2. Predicting Employee Attrition Using Ensemble Models 3. Implementing a Jokes Recommendation Engine 4. Sentiment Analysis of Amazon Reviews with NLP 5. Customer Segmentation Using Wholesale Data 6. Image Recognition Using Deep Neural Networks 7. Credit Card Fraud Detection Using Autoencoders 8. Automatic Prose Generation with Recurrent Neural Networks 9. Winning the Casino Slot Machines with Reinforcement Learning 10. The Road Ahead
11. Other Books You May Enjoy

Understanding the MNIST dataset

Modified National Institute of Standards and Technology (MNIST) is a dataset that contains images of handwritten digits. This dataset is pretty popular in the ML community for implementing and testing computer vision algorithms. The MNIST dataset is an open dataset made available by Professor Yann LeCun at http://yann.lecun.com/exdb/mnist/, where separate files that represent the training dataset and test dataset are available. The labels corresponding to the test and training datasets are also available as separate files. The training dataset has 60,000 samples and the test dataset has 10,000 samples.

The following diagram shows some sample images from the MNIST dataset. Each of the images also comes with a label indicating the digit shown in the following screenshot:

Sample images from MNIST dataset

The labels for the images shown in the preceding...

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