'Nostalgia' is an installation that draws attention to the computational challenges of understanding the human emotion it refers to, and the disparities that lie in its individual and collective interpretations. Through affective computing and machine learning, the underlying system attempts to translate the components of the sentiment's qualitative makeup in quantitative terms. In 'Nostalgia', participants are asked to submit text-based memories, which are then used to calculate, predict and ultimately visualize relative nostalgia scores based on the aggregate of stories collected. However, given the ambiguities and complexity of human self-expression and the necessary precision of computational intelligence, 'Nostalgia' highlights the entanglements of achieving emotional understanding between humans and machines. When a participant submits a memory, the system computes a nostalgia score/index ranging from 0-100 based on an algorithmic model, which is driven by a machine learning algorithm that was trained with texts classified against the Southampton Nostalgia Scale coupled with IBM's Natural Language Understanding API. Many people in the Western world are familiar with the idiom "looking at the world through rose-colored glasses” (Doyle, 2001), and it has a scientific corollary known as rosy retrospection. This notion refers to the tendency for people to remember events and their experiences more fondly or positively than they evaluated them to be at the time of their occurrence (Mitchell, Thompson, Peterson, Cronk, 1997). It is in this vein that the work achieves its visual aesthetic, referring literally to the word "rosy". Both its digital visualization and set of electro-mechanical sculptures demonstrate aspects of its computational understanding through color and time; stronger nostalgia scores correspond with rosier hues throughout and slower motor speeds to hold on to a moment in time.