Common pitfalls faced when working on a Data Science project and how to avoid them
Common pitfalls faced when working on a Data Science project and how to avoid them
I will try to focus on the most common mistakes which people made during the data science projects –
- Using too many Data Science Terms in your Resume – People use to copy others resume which they should avoid
- Not Spending Enough Time on Exploring and Visualizing the Data (Curiosity) – They don’t try to understand the data before visualization
- Not Having a Structured Approach to Problem Solving – They should follow a trusted approach
- Trying to Learn Multiple Tools at Once – Don’t Mix with other tools, one tool at one time
- Not Studying in a Consistent Manner – Please be consistent about your study and be focussed
- Shying Away from Discussions and Competitions – Tyr to take part in more hackathons, competitions, write blogs and try to post questions in communities ( Tableau, SAS, QLIK)
- Not working on Communication Skills – Most important try to speak well be specific and to the point, try to relate with your real-life problem then describe
- Try to apply the methods which you learn
- Focus on the model accuracy – They should focus on the model accuracy ( try to understand the R square and P-value well)
Author – Satyabrata Majhi