I am new to data science/ machine learning world. I know that in Statistics we assume that a certain event/ process has some particular distribution and the samples of that random process are part of some sampling distribution. The findings from the data could then be generalized by using confidence intervals and significance levels.How do we generalize our findings once we learn the patterns in the data set? What is the alternative to confidence levels here?
How are the findings learnt from the data set are generalized compared to Statistics?
machine learning;statistics