How do we quantify uncertainty in deep learning models ?
Neural Networks Everywhere The genesis of Deep Learning began primarily in 2012 when researchers were able to capture the information present in millions of images and accurately predict class labels. This breakthrough was a culmination of multiple scientific developments. Quintessentially, Neural networks are universal functional approximators and this innate quality allows them to applied on diverse problem spaces. This is the fundamental reason behind the pervasive nature of Neural Networks. ...