MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018
Instructor: Gilbert Strang
View the complete course: ocw.mit.edu/18-065S18
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Gradient descent is the most common optimization algorithm in deep learning and machine learning. It only takes into account the first derivative when performing updates on parameters - the stepwise process that moves downhill to reach a local minimum.
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Негізгі бет 22. Gradient Descent: Downhill to a Minimum
Пікірлер: 42