Impact Assessment of Water Quality on Ecosystems with Neural Networks in Python

This tutorial covers:

Generate a dataframe of chemistry with the same index as species

Create an interactive plot

Predict ecosystem variables:

  • Impact of pH on vegetation abundance
  • Impact of Conductivity on vegetation abundance
  • Impact of Dissolved Oxygen on vegetation abundance
  • Impact of Nitrates on vegetation abundance

Video

Key Aspects

There are some key aspect to consider in the effectiveness of neural networks. Some of there are:

  • Consistent data
  • Extensive data records
  • Understanding of the governing rules of the phenomenon
  • Review of the neural network theory

While considering these aspects, you can enjoy this awesome tool for your everyday work.

 

Data

Download the required data for this tutorial on this link:

https://github.com/SaulMontoya/Impact-Assessment-of-Water-Quality-on-Ecosystems-with-Neural-Networks-in-Python

 

For any application of neural networks on a specific field please writo to:

saulmontoya@gidahatari.com

Saul Montoya

Saul Montoya es Ingeniero Civil graduado de la Pontificia Universidad Católica del Perú en Lima con estudios de postgrado en Manejo e Ingeniería de Recursos Hídricos (Programa WAREM) de la Universidad de Stuttgart con mención en Ingeniería de Aguas Subterráneas y Hidroinformática.

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