Interpretable AI is filled with cutting-edge techniques that will improve your understanding of how your AI models function. Focused on practical methods that you can implement with Python, it teaches you to open up the black box of machine learning.
Ajay Thampi is a machine learning engineer at a large tech company primarily focused on responsible AI and fairness.
Probabilistic Deep Learning teaches the increasingly popular probabilistic approach to deep learning that allows you to tune and refine your results more quickly and accurately without as much trial-and-error testing.
Oliver Dürr is professor for data science. Beate Sick holds a chair for applied statistics at ZHAW. Elvis Murina is a research assistant.