Challenge background
The necessary nutrients for plant growth are nitrogen, potassium, and phosphorus. The amount of these minerals in the soil in combination with the weather condition elements can be used to differentiate the type of plat to be harvested at that particular land.
The problem
In this challenge, we will try to address a plant type recommender system using the nitrogen, phosphorus, and potassium values of the soil. We will also consider the amount of temperature, humidity, and altitude in order to make our recommendations more accurate.
Goal of the project
Our primary goal is to create a machine learning model that can accurately recommend the type of plant we need to plant using the nitrogen, phosphorus, and potassium contents of the soil.
Project timeline
- 1
Week 1
Data collection and Data preparation
- 2
Week 2
Training machine learning model
- 3
Week 3
Training the machine learning model and preparing it for implementation
- 4
Week 4
Project completion and submission
What you'll learn
Data science, Machine learning