  Throughout the various ages, facial expressions have become one of the
universal ways of non-verbal communication. The ability to recognize facial
expressions would pave the path for many novel applications. Despite the
success of traditional approaches in a controlled environment, these approaches
fail on challenging datasets consisting of partial faces. In this paper, I take
one such dataset FER-2013 and will implement deep learning models that are able
to achieve significant improvement over the previously used traditional
approaches and even some of the deep learning models.
