Answer:
1 Array languages
2 Assembly languages
3 Authoring languages
4 Constraint programming languages
5 Command line interface languages
6 Compiled languages
7 Concurrent languages
8 Curly-bracket languages
9 Dataflow languages
10 Data-oriented languages
11 Decision table languages
12 Declarative languages
13 Embeddable languages
13.1 In source code
13.1.1 Server side
13.1.2 Client side
13.2 In object code
14 Educational languages
15 Esoteric languages
16 Extension languages
17 Fourth-generation languages
18 Functional languages
18.1 Pure
18.2 Impure
19 Hardware description languages
19.1 HDLs for analog circuit design
19.2 HDLs for digital circuit design
20 Imperative languages
21 Interactive mode languages
22 Interpreted languages
23 Iterative languages
Explanation:
Answer:
Binary Code
Explanation:
All microprocessors and programmable devices understand is Binary Code. These are various combinations of 0's and 1's which when placed together in a sequence represent a set of instructions that the microprocessor can read and understand to complete complex tasks. There are various other programming languages to program these tasks in an easier to read syntax for the programmers themselves but they simply take the written code and convert it into Binary before sending it to the microprocessor.
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.
Answer:
No they are not likely to crash
Explanation:
The video game industry is more advanced than it was back in the 1980s. There have been a great level of improvements in technology in this industry such as things like virtual reality advancements,greater hardware capabilities and alot more capital investments and big players in the industry. This has allowed the industry to grow and become stronger with so much potential, amassing a larger amount of consumers. The crash in the 1980s was a result of limited options in gaming as a result of limited technologies whereby individuals began to switch to personal computers for gaming. This is unlikely to happen now seeing that there have been greater improvements in the industry in terms of gaming technologies and increased variety and options in gaming consoles
