Kothi Madhuri

Food recognition from images is a challenging problem because many food items appear visually similar and often contain multiple ingredients. Lighting conditions, camera angles, and presentation styles further complicate the task. This project proposes an Enhanced Food Detection and Nutritional Inference System that uses artificial intelligence to detect food items from images and estimate their nutritional values. The system integrates computer vision models, vision–language reasoning techniques, and a structured nutrition database to generate nutritional information automatically. The workflow includes image preprocessing, food detection, food identification using AI reasoning, and mapping the detected food items to a nutritional database. The final system provides nutritional insights such as calories and macronutrients to help users better understand their dietary intake

Customer reviews have emerged as a strong source of information in the digital era, which affects brand perception and consumer decision. The presence of millions of reviews created by users on the e-commerce platforms like Amazon offers insightful information on customer preferences, products quality, and overall customer satisfaction. To prevent businesses falling behind in terms of competition and customer focus, this mass of textual data, primarily unstructured, requires a look into. The project is expected to create a machine learning-based project relying on Natural Language Processing (NLP) methods to analyze Amazon reviews and derive meaningful information about customers. The system will be used to analyze sentiments, classify the text and extract the topics in order to know about how the customers feel and trends in their responses. We can also consider advanced NLP models like word embeddings and transformer-based models which can be used to increase the accuracy of the data analysis. The projected result of this project is to have a complete analytical model that assists business to be aware about customer sentiment, product problems and improve decision-making. Using insights that are based on the data, the organizations in question can enhance their customer satisfaction as well as brand perception, along with making their marketing better.