A Framework for movie recommendations using Artificial Intelligence

To provide tailored recommendations that correspond with users' search preferences, recommendation systems assume a critical function. This article presents a machine learning project executed in Python to develop a Netflix recommendation engine. Netflix, a well-known streaming service, provides an extensive library of television shows and movies that are available online at any time. By imposing a monthly subscription fee, the platform secures its profitability. But sustaining user engagement and preventing disengagement are crucially important for the company, and meaningful and relevant suggestion is necessary to achieve it. Netflix uses its recommendation engine to consolidate its services among service providers. That enables it to sell more product, offer more content for users, enhance user's satisfaction, and keep using that platform. Additionally, it provides tremendous information on user preferences, thereby giving the company an even greater understanding of their wishes. This way, by availing diverse movie choices to its users, Netflix makes sure they can make better choices. By using its recommendation engine, Netflix ensures that a more relevant and popular set of movies are offered to the users in order to provide them with better choices and thus, develop an affinity towards the site.