Important Points

  • Developed a ML model which can detect a predefined set of 10 different contaminants present in the waste water with an accuracy of 99.7%.
  • Utilized the Random Forest Classifier algorithm for the classification tasks of the samples.
  • Trained the model with an dataset exceeding 1,50,000 samples, enabling it to learn and adapt to changes.
  • Aqua Alert is able to detect 10 different contaminanted substance which poses a serious global threat to natural ecosystem.
Tools Used : Python, NumPy, Pandas, Matplotlib, Scikit-Learn, Gradio, Hugging Face

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