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The society these days is bounded with inactive and unhealthy lifestyle.  According to the recent studies, there is a rapid increase of individuals suffering and dying from diseases caused by poor diet and unhealthy lifestyle. In view of this, knowing the right kind of food to eat, and the appropriate exercise is essential in achieving good health.  Being fit relates to good health, and healthy living makes life longer and happier. The objective of this study is to develop a system that will recommend its users the appropriate exercise and diet for their daily activities.  Exercise and diet plans were gathered and were validated by experts to ensure utmost level of effectiveness and safety among users.  Linear regression with passive monitoring of user activities was used to estimate and forecast future fitness states of the users.

Data Analytics Enforced Content-Based Fitness Recommender System for Individuals without Allergies and Ailments