Inspiration

We wanted to make an understandable model that had a reasonable performance.

What it does

Accurately predicts delays in order fulfilment.

How we built it

Using ML models with Python, together with data visualitzation tools to better communicate our insights.

Challenges we ran into

Bugs and data cleaning, amogst others.

Accomplishments that we're proud of

A highly accurate model with an easily explainable functionality behind it.

What we learned

The value of organitzation in compressed time frames as well as technical aspects related to ML.

What's next for postgreSQLillo

Using the acquired knowledge to develop new, innovative applications.

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