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Predictive Modeling for Agriculture

IntermediateSkill Level
4.8+
766 reviews
Updated 04/2024
Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.
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PythonMachine LearningProgramming1 hr1 Task1,500 XP23,398

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Project Description

Predictive Modeling for Agriculture

A farmer reached out to you as a machine learning expert seeking help to select the best crop for his field. Due to budget constraints, the farmer explained that he could only afford to measure one out of the four essential soil measures:
  • Nitrogen content ratio in the soil
  • Phosphorous content ratio in the soil
  • Potassium content ratio in the soil
  • pH value of the soil
The expert realized that this is a classic feature selection problem, where the objective is to pick the most important feature that could help predict the crop accurately. Can you help him?

Predictive Modeling for Agriculture

Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.
Start Project
  • 1

    In this project, you will be introduced to two techniques for feature selection and apply them to the farmer's problem. By working on this project, you will gain valuable insights into how machine learning can solve real-world agricultural problems.

Don’t just take our word for it

*4.8
from 766 reviews
81%
19%
0%
0%
0%
  • Djem Andreif
    about 2 hours

  • Marjolein
    about 2 hours

  • Faisal Maulana
    about 3 hours

  • Amit
    about 5 hours

  • Edrian
    about 6 hours

  • Greg
    about 16 hours

    This one was easier to attempt and much more fun then the RAG Application project well done.

Faisal Maulana

Amit

"This one was easier to attempt and much more fun then the RAG Application project well done."

Greg

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