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Machine Learning Solutions

You're reading from   Machine Learning Solutions Expert techniques to tackle complex machine learning problems using Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788390040
Length 566 pages
Edition 1st Edition
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Toc

Table of Contents (19) Chapters Close

Machine Learning Solutions
Foreword
Contributors
Preface
1. Credit Risk Modeling 2. Stock Market Price Prediction FREE CHAPTER 3. Customer Analytics 4. Recommendation Systems for E-Commerce 5. Sentiment Analysis 6. Job Recommendation Engine 7. Text Summarization 8. Developing Chatbots 9. Building a Real-Time Object Recognition App 10. Face Recognition and Face Emotion Recognition 11. Building Gaming Bot List of Cheat Sheets Strategy for Wining Hackathons Index

Understanding the dataset


In this section, we will cover the dataset on which the Deep Learning models have been trained. There are two datasets that are heavily used when we are trying to build the object detection application, and those datasets are as follows:

  • The COCO dataset

  • The PASCAL VOC dataset

We will look at each of the datasets one by one.

The COCO dataset

COCO stands for Common object in context. So, the short form for this dataset is the COCO dataset. Many tech giants, such as Google, Facebook, Microsoft, and so on are using COCO data to build amazing applications for object detection, object segmentation, and so on. You can find details regarding this dataset at this official web page:

http://cocodataset.org/#home

The COCO dataset is a large-scale object detection, segmentation, and captioning dataset. In this dataset, there are a total of 330,000 images, of which more than 200,000 are labeled. These images contain 1.5 million object instances with 80 object categories. All the...

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