<p>This episode is an interview with <a href= "https://people.eecs.berkeley.edu/~tinghuiz/">Tinghui Zhou</a>.  In the recent paper "<a href= "https://people.eecs.berkeley.edu/~tinghuiz/projects/SfMLearner/">Unsupervised Learning of Depth and Ego-motion from Video</a>", Tinghui and collaborators propose a deep learning architecture which is able to learn depth and pose information from unlabeled videos.  We discuss details of this project and its applications.</p>

[MINI] Max-pooling

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.