Aug 2020 - Present
Recommender System is a system that seeks to predict or filter preferences according to the user’s choices. Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and products in general. Recommender systems produce a list of recommendations in any of the two ways –
Content-based filtering: Content-based filtering approaches uses a series of discrete characteristics of an item to recommend additional items with similar properties. Content-based filtering methods are based on a description of the item and a profile of the user’s preferences. It recommends items based on the user’s past preferences(supervised learning).
Collaborative filtering: Collaborative filtering approaches build a model from the user’s past behaviour (i.e. items purchased or searched by the user) as well as similar decisions made by other users. This model is then used to predict items (or ratings for items) that user may have an interest in(unsupervised learning).
TKINTER:
Python offers multiple options for developing a GUI (Graphical User Interface). Out of all the GUI methods, Tkinter is the most commonly used method. It is a standard Python interface to the Tk GUI toolkit shipped with Python. Python with Tkinter is the fastest and easiest way to create GUI applications. Creating a GUI using Tkinter is an easy task.