Machine Learning

I have some agricultural data set. A data scientist should:
1. Find dependencies between indicators and output value and find most meaningful features.
2. Create a prediction model.
3. Maximize output variable based on meaningful prediction model.

Some more details:
The data set includes several indicators of changeable parameters that affect vegetables growing process and also includes gross output as a target variable. Some indicators may affect directly, some may need aggregation over time.

Finally we should be able to:
1. Predict future output based on applied parameters.
2. Maximize output based on optimal parameter set.

This is a first POC of this project. If the data set shows something meaningful, we will be looking forward to implement this solution in production.
About the recuiter
Member since Mar 14, 2020
Vehicloo
from Valga, Estonia

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