Authors - Archana L. Rane, Sanskruti R. Talele, Rashika A. Ghavate, AditiS.Khairnar, Harisha A. Chothani Abstract - Nowadays, the world is increasingly focused on health care, with hair care emerging as a key aspect of personal well-being. Many people face confusion when selecting the best shampoo based on their scalp and hair health. The purpose of this study is to provide a natural alternative to conventional shampoos by incorporating eggshell powder, a readily available, eco-friendly resource, into future hair care formulations. A comprehensive study was conducted to evaluate various shampoos currently available and to identify the benefits of eggshell powder. This study highlights the potential of eggshell powder in enhancing shampoo production. Machine learning algorithms such as Naive Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest were employed to analyze manufacturing parameters and optimize the absorption of eggshell powder. The results of the analysis revealed varying accuracies for each model: Naive Bayes (52%), KNN (71%), SVM (72%), and Random Forest (82%). These techniques allowed for precise adjustments to ingredient concentrations and interactions, improving the overall efficacy of the shampoo. The results demonstrate that shampoos formulated with eggshell powder offer several advantages, including stronger hair, better moisture retention, and enhanced scalp health. Additionally, eggshell powder proved to be a sustainable material, aligning with growing consumer demand for environmentally friendly products. This study highlights the potential of using natural resources and machine learning to drive data-driven improvements in hair care formulations, offering a promising alternative to conventional products while meeting the increasing preference for sustainability.
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