• Aketi Thanuja
• Sri Dantuluri Aashika
• Kalidindi Manaswi
• Balagam Avinash
• Vijaya Bharathi Manjeti

Recommender systems are a category of content filtration. A recommendation system's main goal is to provide software recommendations for items that the user could find useful. The suggestions span a broad variety of topics, such as what to buy, what to watch, and where to go on vacation. Climate, events, catastrophic infections such as coronavirus, as well as other variables all occur on a regular basis. The proportion of people adopting digital marketing has gone up significantly as the Net has spread. With an ever increase volume of online info, recommendation engines have proven to be an effective method of coping with information explosion. The importance of recommendation cannot be overstated, given their ubiquitous use in these web apps and their capacity to solve a variety of problems associated with over-choice. Deep learning has generated considerable interest in an array of educational domains, particularly machine learning and natural language interpretation, owing to its superior accuracy as well as the appealing feature of learning feature representations from scratch. Deep learning's impact is as broad, with fresh research showing its efficacy in information retrieval and recommender systems. In particular, both textile and garment businesses have experienced enormous growth in recent years. A successful recommending system is needed for e-commerce sites with multiple alternatives to filter, organize, and quickly deliver pertinent product content and information to clients. Consumers, on the other hand, are having difficulty locating their preferred apparel items among many of the enormous array of options available on the Internet. As a workable solution, we present a deep learning-based fashion-brand recommendation system. This method increases the likelihood of a user discovering his or her preferred apparel items. FRSs (fashion recommendation systems) recently piqued the interest of fast fashion merchants since they provide a more personalize customer experience for clients. Due to technological advancements, this field of AI technology seems to have a great deal of potential in image enhancement, interpretation, categorization, and segmentation.

Deep Learning, Recommender Systems, Enhancement, Interpretation, Categorization, Segmentation.

"Fashion Recommendation System using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.g583-g587, April-2022, Available :http://www.jetir.org/papers/JETIR2204684.pdf

"Fashion Recommendation System using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppg583-g587, April-2022, Available at : http://www.jetir.org/papers/JETIR2204684.pdf