Causal Inference with Machine Learning: An Introduction with Ashley Naimi

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Dive into the first hour of Dr. Ashley Naimi's "Machine Learning for Estimating Causal Effects" seminar!
About this seminar:
In this 14-hour hands-on seminar, Dr. Naimi will show you how to minimize biases that result from improper use of machine learning methods to answer practical questions about cause-effect relations in non-experimental data. Key topics include using machine learning to relax modeling assumptions, avoiding problems resulting from the “curse of dimensionality," employing cutting-edge “double-robust” machine learning methods, and estimating different treatment effects in real and simulated data. The course emphasizes practical application, offering numerous coding examples to help you develop a deep understanding of these techniques.
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