VIDEO RECOMMENDATION ALGORITHM WITH MACHINE LEARNING TO INCREASE USERS' CONSUMPTION TIME ON THE YOUTUBE PLATFORM AND IMPROVE THE RECOMMENDATIONS OFFERED

This work aims to develop an Artificial Intelligence for analyzing the data from the YouTube platform through the users' video viewing history and to demonstrate how Machine Learning is capable of classifying users based on their interests using a Classification algorithm. The analysis generates recommendations of videos that align with the user's preferences, by comparing them with our database and identifying the best recommendations. In this article, we will detail the aspects of AI, the technologies used, the extraction methodology and the extracted data. The obtained results serve as valuable insights for YouTube itself or for content creators on this and other similar platforms in the Entertainment market, aiming to better understand their audience and how to reach more people through user behavior data.