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學生對 Coursera Project Network 提供的 Creating Custom Callbacks in Keras 的評價和反饋

66 個評分


In this 1.5-hour long project-based course, you will learn to create a custom callback function in Keras and use the callback during a model training process. We will implement the callback function to perform three tasks: Write a log file during the training process, plot the training metrics in a graph during the training process, and reduce the learning rate during the training with each epoch. 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, Neural Networks, and the Keras framework. 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....

1 - Creating Custom Callbacks in Keras 的 8 個評論(共 8 個)

創建者 Atulya K


You learn how to update learning rate and plot validation and train accuracy dynamically in jupyter notebook. This is a very targeted course so if you don't know how to train ML models on keras or don't know ML at all this course is not for you.

The code needs to be slightly modified for newer version of keras and tensorflow but works perfectly in the Rhyme VM. Thanks for the code template, I can easily incorporate this bit in my future ML projects.

創建者 Anderson J S d O


Good explanation based upon in class to show how we can use keras

創建者 olivier c


Superb. Answers to a real need !

創建者 Doss D


Thank you very much

創建者 Kamlesh C



創建者 tale p



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創建者 gowthaman


Good to knowledge