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The Art of Solving Any Data Science Problem — Simple Tips For A Better Outcome
Unspoken Advice To Avoid Trouble and Increase Your Chances of Success
Most people interested in data science learn about tools and technology to solve data science problems. They are absolutely necessary to build a solution. But, remember, it is just not enough. To come up with an efficient solution, one needs to learn the art of problem-solving. There are many courses to teach about the tools and technology in data science. There aren’t many courses on how to solve a data science problem.
In this article, my aim is to use real-world use cases to help you understand the key aspects of solving a data science problem. We will also see how these would assist in identifying and solving the core business problem. Also, how they assist in avoiding common pitfalls that lead to issues.
To make sure the concepts discussed here are easier to understand, I will use customer churn in telecommunications as an example.
Problem Conceptualization
