Recommendation system for anime using machine learning algorithms

These days, many people watch anime, especially the younger generations. With so many different sorts of programming available, this specialist area of the entertainment industry is drawing an increasing number of people. The word “anime,” which was derived from the word “animation,” has a growing fan following all over the world. The anime industry has been growing rapidly in recent years, bringing in billions of dollars annually. Significant streaming providers like Netflix and Amazon Prime are paying attention to this industry. Researchers are working hard to apply machine learning algorithms to offer the viewer with the appropriate anime because it is currently a popular trend among the younger generation. The purpose of the research presented in the research article that follows is to further current field reserch. From Kaggle, two datasets have been utilized. The first dataset for an anime comprises 7 columns and 12293 rows. The second rating dataset comprises 3 columns and 7813735 rows. Anime may be rated by users, who can then add it to their finished list. The top 15 matching suggestions and forecasted ratings were then obtained using machine learning approaches (content-based filtering, collaborative filtering, and popularity-based filtering).