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You're reading from  Mastering OpenCV 4 with Python

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Published inMar 2019
Reading LevelExpert
PublisherPackt
ISBN-139781789344912
Edition1st Edition
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Alberto Fernández Villán
Alberto Fernández Villán
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Alberto Fernández Villán

Alberto Fernndez Villn is a software engineer with more than 12 years of experience in developing innovative solutions. In the last couple of years, he has been working in various projects related to monitoring systems for industrial plants, applying both Internet of Things (IoT) and big data technologies. He has a Ph.D. in computer vision (2017), a deep learning certification (2018), and several publications in connection with computer vision and machine learning in journals such as Machine Vision and Applications, IEEE Transactions on Industrial Informatics, Sensors, IEEE Transactions on Industry Applications, IEEE Latin America Transactions, and more. As of 2013, he is a registered and active user (albertofernandez) on the Q&A OpenCV forum.
Read more about Alberto Fernández Villán

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The Keras library

Keras (https://keras.io/) is an open source, high-level neural network API written in Python (compatible with Python 2.7-3.6). It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML, and was developed with a focus on enabling fast experimentation. In this section, we are going to see two examples. In the first example, we are going to see how to solve a linear regression problem using the same input data as the TensorFlow example in the previous section. In the second example, we will classify some handwritten digits using the MNIST dataset in the same way we also performed in the previous section with TensorFlow. This way, you can clearly see the differences between the two libraries when solving the same kind of problems.

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Mastering OpenCV 4 with Python
Published in: Mar 2019Publisher: PacktISBN-13: 9781789344912

Author (1)

author image
Alberto Fernández Villán

Alberto Fernndez Villn is a software engineer with more than 12 years of experience in developing innovative solutions. In the last couple of years, he has been working in various projects related to monitoring systems for industrial plants, applying both Internet of Things (IoT) and big data technologies. He has a Ph.D. in computer vision (2017), a deep learning certification (2018), and several publications in connection with computer vision and machine learning in journals such as Machine Vision and Applications, IEEE Transactions on Industrial Informatics, Sensors, IEEE Transactions on Industry Applications, IEEE Latin America Transactions, and more. As of 2013, he is a registered and active user (albertofernandez) on the Q&A OpenCV forum.
Read more about Alberto Fernández Villán