Answer:
99.
Step-by-step explanation:
A palindrome number is one that can be read in the same way both from the front and from the back. A clear example is the number 242, which starts and ends in the same way from the front or back.
Between 10 and 100, there are 9 palindromes, from 11 to 99. In turn, between 100 and 200, 200 and 300 and so on, each hundred has within it 10 palindromes (101, 111, 121, 131, 141 , 151, 161, 171, 181 and 191, for example).
Therefore, considering the 9 hundreds between 100 and 1000, there will be 90 palindromes, which added to the 9 between 10 and 100 give a total of 99 palindromes.
28.7083333333...
But you could also round it up to 29.
Answer:
Bias is the difference between the average prediction of our model and the correct value which we are trying to predict and variance is the variability of model prediction for a given data p[oint or a value which tells us the spread of our data the variance perform very well on training data but has high error rates on test data on the other hand if our model has small training sets then it's going to have smaller variance & & high bias and its contribute more to the overall error than bias. If our model is too simple and has very few parameters then it may have high bias and low variable. As the model go this is conceptually trivial and is much simpler than what people commonly envision when they think of modelling but it helps us to clearly illustrate the difference bewteen bias & variance.
Frequency describes the number of waves that pass a fixed place in a given amount of time.
So B is 6x bigger than figure A and A is only half the size of B
