Answer:
File transfer protocol (FTP)
Explanation:
An information can be defined as an organized data which typically sent from a sender to a receiver. When a data is decoded or processed by its recipient it is known as information.
Generally, there are several channels or medium through which an information can be transmitted from the sender to a receiver and vice-versa. One of the widely used media is the internet, a global system of interconnected computer networks.
There's a standard framework for the transmission of informations on the internet, it is known as the internet protocol suite or Transmission Control Protocol and Internet Protocol (TCP/IP) model. One of the very basic rule of the TCP/IP protocol for the transmission of information is that, informations are subdivided or broken down at the transport later, into small chunks called packets rather than as a whole.
The three (3) main types of TCP/IP protocol are;
I. HTTP.
II. HTTPS.
III. FTP.
File transfer protocol (FTP) is used between two or more computers. One computer sends data to or receives data from another computer directly through the use of network port 20 and 21.
Answer:
Multiple devices can be connected
Answer:
a. Dr. Franklin wishes he were the one who had invented the new web application.
b. If he were willing to submit the proposal, we might win the bid.
Explanation:
The subjunctive mood is when we're talking about wishes, doubts, and possibilities, in this case, we have two examples, where Dr. Franklin wishes to invent the new web application, and the other sentence is a possibility because he believes that they can win the bid. The last example is an affirmation.
Answer:
Collaborative filtering
Explanation:
This is one out of five on the Recommender system apart from most popular items, Association and Market Basket based Analysis, Content-based analysis, self and hybrid analysis where we use both content-based and collaborative based approach together. And the Recommender system is a very important topic in Data science. For this question, remember that Collaborative filtering focuses on user and various other user's choices which are mathematically alike to concerned users, and which we find with the study of a large data set. Thus, we can predict from our above study that what are going to be likes of concerned users, and at the item level, whether that item will be liked by the concerned user or not. And this is prediction, and we use this approach in Machine learning these days. For this question, and as mentioned in question the requirements, answer is Collaborative filtering.
