Agro Regression Process with ML


AGRO Regression with ML: Harnessing machine learning to predict crop production based on environmental parameters, optimizing agricultural practices.

Project Information

AGRO Regression with ML is a cutting-edge project that utilizes machine learning algorithms, such as Decision Tree Regression, Random Forest Regression, XGB Regression, and Neural Network, to predict crop production based on key parameters like Temperature, Humidity, and Rainfall. Through comprehensive analysis and accuracy evaluation, the project identifies the best algorithm for precise crop production estimation. All analysis and details are performed using Python and PyCharm, providing a powerful and user-friendly environment for agricultural forecasting. Empower your farming practices with AGRO Regression with ML and optimize crop production like never before.

Additional Information

Hardware :

  • Sensors : Humidity and temperature sensor(DHT11), Rainfall measurement (ultrasonic sensor HCSR04)
  • Arduino


  • Arduino IDE
  • Python
  • Pycharm


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