Water-Quality-Model-

Objective:

• To develop a model using TensorFlow/Keras for analyzing water quality data and predicting water quality .
• Develop an interface for the project Use a mobile app and/or Web app using React/ Python

About Dataset

This dataset contains water quality measurements and assessments related to potability, which is the suitability of water for human consumption. The dataset's primary objective is to provide insights into water quality parameters and assist in determining whether the water is potable or not. Each row in the dataset represents a water sample with specific attributes, and the "Potability" column indicates whether the water is suitable for consumption.

Columns:

• pH: The pH level of the water.
• Hardness: Water hardness, a measure of mineral content.
• Solids: Total dissolved solids in the water.
• Chloramines: Chloramines concentration in the water.
• Sulfate: Sulfate concentration in the water.
• Conductivity: Electrical conductivity of the water.
• Organic_carbon: Organic carbon content in the water.
• Trihalomethanes: Trihalomethanes concentration in the water.
• Turbidity: Turbidity level, a measure of water clarity.
• Potability: Target variable; indicates water potability with values 1 (potable) and 0 (not potable).

Objective:

The main objective of this dataset is to assess and predict water potability based on water quality attributes. It can be used for evaluating the safety and suitability of water sources for human consumption, making informed decisions about water treatment, and ensuring compliance with water quality standards.

Data Source:

The data was collected from here

Credits go to them.

how to use the Repo

The Project is Divided into Backend , frontend and Model

For the Backend, it contains the code fastapi server we are using

For the Frontend, it contains the code Nextjs server we are using to interact with the backend that contains the model.

For the Model, it contains the code Jupter Notebook server we are using to build the model and also make predictions for the model

Frontend Documentation

The Project Documentation, OUr frontend is fully integrated and build with Nextjs

To get started,

1. Download the project

git clone https://github.com/RuthBiney/Water-Quality-Model-.git

2. Head the frontend folder and also get into the predict-app

cd frontend


then

cd predict-app

3. Install the dependencies

npm install

4. run the server to start prediction and info about app

npm run start 

Backend Documentation

The Project Documentation, Our backend is fully integrated and build with fastapi

To get started,

1. Download the project

git clone https://github.com/RuthBiney/Water-Quality-Model-.git

2. navigate to the backend

cd backend

3. create a new virtual environment

python -m venv <name of env> 

eg. 
python -m venv env

4. Install the dependencies needed for the virtual environment

pip install -r requirements.txt

5. Run the server to be able to interact with the server

fastapi dev main.py

Model

Our model is a simple python code that using tensor and keras to build the model that is used to predict the water portability

Getting started with the code.

To be able to run the model or work with the model

1. Build a virtual env

python -m venv env

2. install the dependencies

pip install -r requirements.txt

3. Run the model

• You can run the model using the jupyter notebook with the name of model.ipynb
• Or you can choose to run the model using the scrip in the water_quality_prediction.py

To be able to run the code
python water_quality_prediction.py

Our Data and Model Explanation

Explanations

Authors and contributors

• Kayongo Johnson Brian - [email protected] - Github Profile
• Joak Buoy Gai - [email protected] - Github Pofile
• Ruth Senir Biney - [email protected] - Github Profile
• John Odai Obodai