Automatic Differentiation with TensorFlow

In this tutorial we learn how automatic differentiation works in TensorFlow 2. This is a key technique for optimizing machine learning models.

Automatic differentiation allows us to estimate partial derivatives of functions numerically using the chain rule. This process is essential for gradient descent and backpropagation.

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[shivvratpandey]

An easy tutorial for beginners.
thank u so much

[cassidymentus]

Good video. One tip might be to zoom in a bit because people may watch these on tv screen.

[ywk]

may I ask what the assert dx_dy==0is for??