Machine_learning-final_project

Like the saying goes, “A healthy people, is a healthy nation.” For people to stay healthy, it is important that some measures of hygiene are considered when handling food and drinks. Food hygiene can therefore be defined as the handling, preparing, and storing food or drinks in a way that best minimizes the risk of consumers becoming sick from the food-borne disease. The overall purpose of food hygiene is to prepare and provide safe food and consequently contribute to a healthy and productive society. The Federal Ministry of Agriculture and L’alimentation, France took the initiative towards boosting the confidence of the people regarding the level of sanitary measures maintained in various food chain (restaurants, canteens, and slaughterhouses, etc..) in France. The publication of the result of health checks in the food sector is a legitimate expectation of citizens which contributes to improving consumer confidence. Provided by the law of the future for agriculture, food, and forestry, of October 13, 2014, this measure is part of an evolution towards greater transparency of state action. Alim’confiance, the dataset on which we worked on comes from a certified public service. On its application as well as its website www.alim-confiance.gouv.fr , consumers can have access to the results of health checks carried out in all establishments in the food chain. The result allows you to know the overall level of hygiene of the food establishment and gives you an idea of compliance with hygiene standards: cleanliness of premises and equipment, hygiene of staff and handling, respect for the supply chain. Various Machine Learning ML have been applied on sanitary, health, biological data and more. Machine learning procedures will be carried out on Alim’Confiance data to classify the various food chain according to their level of compliance into Satisfactory, Very Satisfactory, To improve, and To be Corrected Urgently.