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Opiniones y comentarios de aprendices correspondientes a Project: Image Classification with CNNs using Keras por parte de Rhyme

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2 revisiones

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In this 1-hour long project-based course, you will learn how to create a Convolutional Neural Network (CNN) in Keras with a TensorFlow backend, and you will learn to train CNNs to solve Image Classification problems. In this project, we will create and train a CNN model on a subset of the popular CIFAR-10 dataset. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with python and convolutional neural networks. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....
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1 - 3 de 3 revisiones para Project: Image Classification with CNNs using Keras

por vamsilakshman

Apr 02, 2020

This project is helpfull for students

por Jhuma

Mar 19, 2020

Thank you . It is really helpfull

por Partheepan

Apr 09, 2020

very useful