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Avis et commentaires pour d'étudiants pour Classification of COVID19 using Chest X-ray Images in Keras par Coursera Project Network

32 évaluations

À propos du cours

In this 1 hour long project-based course, you will learn to build and train a convolutional neural network in Keras with TensorFlow as backend from scratch to classify patients as infected with COVID or not using their chest x-ray images. Our goal is to create an image classifier with Tensorflow by implementing a CNN to differentiate between chest x rays images with a COVID 19 infections versus without. The dataset contains the lungs X-ray images of both groups.We will be carrying out the entire project on the Google Colab environment. Please be aware of the fact that the dataset and the model in this project, can not be used in the real-life. We are only using this data for educational purposes. By the end of this project, you will be able to build and train the convolutional neural network using Keras with TensorFlow as a backend. You will also be able to perform data visualization. Additionally, you will also be able to use the model to make predictions on new data. You should be familiar with the Python Programming language and you should have a theoretical understanding of Convolutional Neural Networks. You will need a free Gmail account to complete this project. Note: 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....

Meilleurs avis


21 nov. 2021

I liked the course as it gives the complete picture of how to make prediction using convolutional neural network. Discussion forum is not so active is a negative point.


20 nov. 2020

It was a very good and practical project.

The subject was completely related to the current situation and I really liked this project.

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par Hamed M

21 nov. 2020

par sunita p

22 nov. 2021

par Maryam G

10 août 2021

par Mann B

11 avr. 2021

par Muhammad M

26 déc. 2020

par Sixto R

19 mai 2021

par NG, S L

20 févr. 2021

par Lorrain G S

6 juil. 2021

par Aniket Y

27 août 2021