Day 22 of acing and mastery of data science  interview and concept.

Day 22 of acing and mastery of data science interview and concept.

1 What is the 80/20 rule? How is it important to model validation?

2 Before applying machine learning algorithms, what are the steps for data wrangling and data cleaning?

3 Can you explain the difference between the K Nearest Neighbors (KNN) algorithm and k-means clustering?

4 Can you explain the difference between a histogram and a box plot?

5 What’s your approach to creating a logistic regression model?

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