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Un-Answered Questions { Data Science }
What makes the difference between “long” and “wide” format data?
How and by what methods data visualizations can be effectively used?
How regularly must an algorithm be updated?
How often should an algorithm be updated?
What prior subject is required to become a data analyst?
How do you define data science?
How have you overcome a barrier to finding a solution?
Why is data cleaning essential in data science?
What is cross-validation?
What is meant by selection bias?
List the variants of backpropagation?
What are eigenvectors and eigenvalues?
Now companies are heavily investing their money and time to make the dashboards. Why?
What are an eigenvalue and eigenvector?
What are outlier values and how do you treat them?
