Given two schemas S and T where S has 10 Tables and 45 elements while T has only one Table with 4 attributes. How many machine learning classifiers do you need to train in order to match elements in the two schemas? Explain how to get the training data for training one of these classifiers.

Data access, business logic, data presentation, and user interaction are all kept distinct using the Model-View-Controller design pattern. Additionally, it distinguishes data presentation from user interaction. Discuss or provide your thoughts on this explanation.

Create an ER diagram that correctly describes the database for exams at Campus in Bäcksvängen in accordance with the following description: (Own assumptions must be clearly described.) Staff for various functions are involved in the exams. All staff have a full name and a unique staff code. Some people are examiners on one or more courses. A course has one name and one unique ladok code. For a course, you can add up its points based on the associated elements. One part is part of a course (for example an exam, a laboratory or project). A course can have several different parts. An element has a name, a description, a torque code, one point and two or more grades (eg: U, G, VG). An element can only belong to one course. Since the database is to process the exams, it is obvious that a part like described as an examination has an examination opportunity that is identified, among other things, by the date, start time, end time and that it is possible to calculate total writing time. A…

.What is the precise difference between a seamless model and a layered model when it comes to VES modelling?