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This is Backpropagation Neural Network project using QCM Sensor Alcohol Dataset to be predicted with 5 different classes {octanol, propanol, butanol, propanol and isobutanol}using that neural network

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QCM Sensor Alcohol Dataset
QCM Sensor Alcohol Dataset
 
 
.gitattributes
.gitattributes
 
 
BPNN.ipynb
BPNN.ipynb
 
 
Backpropagation Using Pytorch and Google Colab.ipynb
Backpropagation Using Pytorch and Google Colab.ipynb
 
 
Data Preprocessing & Analyzing .ipynb
Data Preprocessing & Analyzing .ipynb
 
 
Dialysis1_Clean_Noheader.csv
Dialysis1_Clean_Noheader.csv
 
 
Dialysis1_Clean_Noheader.xlsx
Dialysis1_Clean_Noheader.xlsx
 
 
Neural Network Using Keras .ipynb
Neural Network Using Keras .ipynb
 
 
QCM10(cleaned)(without header).csv
QCM10(cleaned)(without header).csv
 
 
QCM10(cleaned).csv
QCM10(cleaned).csv
 
 
README.md
README.md
 
 
Splitting Training and Testing Dataset.ipynb
Splitting Training and Testing Dataset.ipynb
 
 
testing(without header).csv
testing(without header).csv
 
 
testing.csv
testing.csv
 
 
training(without header).csv
training(without header).csv
 
 
training.csv
training.csv
 
 

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Title: QCM Sensor Alcohol Prediction using BPNN Project

Project Description: This project is to determine the accuracy of the model that trained using BPNN algorithm to predict the type of the alcohol. Details: This project provided with cleaned dataset which used for model training with BPNN algorithm. The labels were the type of the alcohol (Propanol, Butanol etc.) and the features were the concentrations of the alcohol. The type of the alcohol determined by the concentration of the alcohol in which this is multiclass classification

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This is Backpropagation Neural Network project using QCM Sensor Alcohol Dataset to be predicted with 5 different classes {octanol, propanol, butanol, propanol and isobutanol}using that neural network

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backpropagation-learning-algorithm multiclass-classification

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