What are learning rate schedules in machine learning?
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What are learning rate schedules in machine learning?
Learning rate schedules are strategies to adjust the learning rate during training to improve model performance.
Why is it important to adjust the learning rate?
Adjusting the learning rate helps in converging faster and avoiding local minima, leading to better model accuracy.
Can you give examples of different types of learning rate schedules?
Sure! Common types include Step Decay, Exponential Decay, and Cyclical Learning Rates.
How do I implement a learning rate schedule in TensorFlow?
You can use the tf.keras.callbacks.LearningRateScheduler to adjust the learning rate during training.
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