Machine learning (ML) data can be represented in the following forms:
1. Matrix and Spatial.
2. Scalar and Vector.
Machine learning (ML) is also referred to as Artificial intelligence (AI) and it can be defined as a subfield in computer science which is focused on the use of computer algorithms to build a smart computer-controlled robot that has the ability (capacity) to automatically perform and handle tasks that are exclusively designed to be performed by humans or by using human intelligence.
Generally, the data that are generated and used in machine learning (ML) can be represented in the following forms:
Read more on machine learning (ML) here: brainly.com/question/25523571
Answer: Suppose that the starting salaries for faculty at Super University ... distribution with mean of $80,000 and standard deviation of $10,000. ... chosen starting faculty member has a salary greater than $90,000? ... If a teacher is selected at random, find the probability that he or she makes more than $36,000.
Explanation:
Here’s the answers, down there
Using the appropriate sample size formula, the minimum number of samples required is 267
<u>Using</u><u> </u><u>the</u><u> </u><u>relation</u><u> </u><u>:</u>
- N = [(Z² × pq) / e²]
- e = Error Margin = 0.06² = 0.0036
- p = 0.5
- q = 1 - 0.5 = 0.5
- Zcritical at 95% = 1.96
<u>Substituting the values into the equation</u> :
N = [(1.96² × (0.5 × 0.5)) / 0.0036]
N = (0.9604 / 0.0036)
N = 266.777
N = 267
Hence, the minimum number of samples required is 267
Learn more : brainly.com/question/25587684