Answer:
Virtualization is the technology that is used to create virtual representation and version of the different devices like software, many storage devices and server.
It also help in organize the working framework where the structure isolates the asset into at least one execution situations.
The benefits of using the virtualization on the single machine are:
- The virtualization increased the productivity when it used in the cluster environment.
- We can able to access the different resources faster.
- The data center management is simple while using the virtualization in the cluster environment.
The drawback of using virtualization on single machine are:
- The virtual machine is less efficient as compared to the real machines.
- The virtual machine indirectly access the computer hardware system so that is why it is less efficient and also consume more power to run the system.
Answer:
1. The reason hunting seasons are displayed all over the world in cave paintings is because of the necessity to hunt. Ancient people everywhere were nomads that relied on wild animals for the majority of their calories. The paintings likely served as an expression of the importance of hunting to their culture. It could have also been used as educational material for very young children to learn about hunting as well as its importance to their community.
Explanation:
I can't do 2nd because the image was cut off, sorry.
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.
I don’t think it will work sadly. You can probably accumulate points though on your pre existing account. Hope that helps!
