Predictive Analytics of Performance of India in the Olympics using Machine Learning Algorithms

India is a country which all the time maintained an exciting pitch and an intense exhilaration for sports. Different reasons have been insinuated for India's lack of tendency to stand atop the podium in the Olympics. Natural endowment can take the athletes only to some extent, but support and encouragement in either financial, emotional or physical form are essential aspects that are necessary to an athlete and without them, the source can often be hopeless. The potential of education is substantial, and sports are considered as a source of relaxation and amusement for millions of youth who are aspiring to be at the top of their class in a country where there are millions of unemployed. The combination of this with terrible food habits, inefficient coaching, bad rehab facilities, increase in competition in schools, shortfall of exercise with physical education and long commutes from work results in many talents getting wasted. Despite all this, we see that India's cricket team is considered as one of the world's best cricket teams of all time. But at the same time we are not able to bring the same commitment and rectitude to the other sports, Olympics in particular. When all the nations are ranked in the order of the number of medals they have won over the years, India ranks at fifty fifth position. To understand the medal deficiency, various attributes are considered. This study, by using Data Science and Machine Learning algorithms, builds a model for predicting why India performs well or poorly in the Olympics by taking into account country-wise GDP, population, Gini index, health and education expenditures, literacy rate and prevalence of undernourishment as the features assuming that they contribute to the performance of the athletes and their effect is studied.