Answer:
D. Refrigerants
Explanation:
In the United States of America, the agency which was established by US Congress and saddled with the responsibility of overseeing all aspects of pollution, environmental clean up, pesticide use, contamination, and hazardous waste spills is the Environmental Protection Agency (EPA). Also, EPA research solutions, policy development, and enforcement of regulations through the resource Conservation and Recovery Act .
The Clean Air Act Amendments of 1990 prohibit service-related releases of all refrigerants such as R-12 and R-134a. This ban became effective on the 1st of January, 1993.
Refrigerants refers to any chemical substance that undergoes a phase change (liquid and gas) so as to enable the cooling and freezing of materials. They are typically used in air conditioners, refrigerators, water dispensers, etc.
Copyright is when someone is given the right to print, publish or make a film.
Answer:
8 Standard Computer Components and What They Do
Explanation:
Motherboard. The motherboard is an important computer component because it’s what everything else connects to!
Power Supply. True to its name, the power supply powers all other components of the machine.
Central Processing Unit (CPU)
Random-access Memory (RAM)
Hard Disk Drive / Solid State Drive.
Video Card.
Optical Drives.
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.
