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1
Intro
2
WRITING A NUMERIC PROGRAM
3
RATE OF CHANGE AS A SLOPE
4
AUTOMATIC DIFFERENTIATION IN PYTHON
5
PLOTTING DERIVATIVES
6
EDGES IN IMAGES
7
OPTIMIZATION WITH JAX
8
GRADIENT DESCENT
Description:
Explore automatic differentiation in Python through this 19-minute PyCon US talk. Gain intuition for derivatives and gradients, and discover their applications in optimization and computational art. Learn to use libraries like jax, TensorFlow, and PyTorch for automatic differentiation. Understand the concept of rate of change, see how to plot derivatives, detect edges in images, and implement gradient descent. Compare different methods for computing derivatives in Python and their respective advantages.

Getting Started with Automatic Differentiation

PyCon US
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