Data Science: Ask a Sharp Question

01_Ask a question your data can answer

  1. Ask a Sharp question
  2. Target Data
  3. Reformulate your question.

02_Ask a Sharp Question

05_target data

Above examples of answers are called a target.

A target is what we are trying to predict about future data points, whether it’s a category or a number.

If you don’t have any target data, you’ll need to get some. You won’t be able to answer your question without it.

06_Reformulate your question

Consider the question, “Which news story is the most interesting to this reader?” It asks for a prediction of a single choice from many possibilities – in other words “Is this A or B or C or D?” – and would use a classification algorithm.

But, this question may be easier to answer if you reword it as “How interesting is each story on this list to this reader?” Now you can give each article a numerical score, and then it’s easy to identify the highest-scoring article. This is a rephrasing of the classification question into a regression question or How much?

Check out the following link:

https://docs.microsoft.com/en-us/azure/machine-learning/studio/data-science-for-beginners-ask-a-question-you-can-answer-with-data

https://gallery.cortanaintelligence.com/