Prediction systems

Monthly Challenge – Sofia Air – Solution – Kung Fu Panda

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12 thoughts on “Monthly Challenge – Sofia Air – Solution – Kung Fu Panda

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    I would recommend importing the Jupyter notebook (ipynb file) directly into the platform. Furthermore, in the section “Data Understanding – Preliminary Analysis” there is too much “how” you work with the data and not enough “why” you do it in the first place. What is the “goal” of each step in the analysis? Keep the good work ! 🙂

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      Thanks! I will try to improve the “why” part. Basically the goal preliminary analysis part is to get an understanding of the data, which data is relevant for our purpose and what part of the data we should further use.

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    Unfortunately your solution is defined in Python and our team is new to this program so we are not sure whether we can give you a specific evaluation or comment. Keep working, looks nice 🙂 – Team Yagoda

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    Your work on Week 2 is pretty good! We noticed that you only filtered the data on P10 particles. There are also serious outliers in temperature and pressure if you are going to use them as explanatory variables for P10. As a suggestion from our team, you can trace the stations that emit false observations and turn them off from next steps of the analysis.
    We really like your visualizations and we are looking forward for your next week solution!
    Team Kiwi (:

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