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Creating Custom Callbacks in Keras

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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.

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Unlock the power of custom callbacks in Keras with this engaging project-based course designed for intermediate learners. In just 1.5 hours, you'll gain hands-on experience in developing your own callback functions and integrating them seamlessly into your model training workflow. Guided by expert instruction from Coursera, this focused training empowers you to enhance and optimize your machine learning models effectively. Best of all, you can access this valuable knowledge for free. Perfect for those looking to deepen their understanding of Keras and take their personal development to the next level.