Why average can get your predictions very wrong (ep. 102)

Whenever people reason about probability of events, they have the tendency to consider average values between two extremes. In this episode I explain why such a way of approximating is wrong and dangerous, with a numerical example. We are moving our community to Slack. See you there!    

Activate deep learning neurons faster with Dynamic RELU (ep. 101)

In this episode I briefly explain the concept behind activation functions in deep learning. One of the most widely used activation function is the rectified linear unit (ReLU). While there are several flavors of ReLU in the literature, in this episode I speak about a very interesting approach that keeps computational complexity low while improving performance quite consistently. This episode is supported by pryml.io. At pryml we let companies share confidential data. Visit our website. Don't forget to join us on discord channel to propose new episode or discuss the previous ones.  References Dynamic ReLU https://arxiv.org/abs/2003.10027