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Causal AI introduces the tools, techniques, and algorithms of causal reasoning for machine learning.
This unique book masterfully blends Bayesian and probabilistic approaches to causal inference with practical hands-on examples in Python.
Along the way, you’ll learn to integrate causal assumptions into deep learning architectures, including reinforcement learning and large language models.
You’ll also use PyTorch, Pyro, and other ML libraries to scale up causal inference.
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