Predictive Modeling for Agriculture

Intermedio

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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Project Description

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?

Project Tasks

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.

Technologies

Python

Topics

Machine Learning Programming

Prerrequisitos

Supervised Learning with scikit-learn

Mohammed Abufouda

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