- This project has tried with SVM, Logistic Regression and XGBoosting ML algorithms
- If wanted to see App Please click here
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Password strength data was collected on the Kaggle and this dataset contains 80000 amount of observation as well as two featuresn which are password and strength. This strength has three level which are low, medium and strong.
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The dataset used can be downloaded Here
- All the dependencies and required libraries are included in the file requirements.txt
- Clone the repo
- Change your directory to the cloned repo
- cd Password-Strength-Prediction-Deployment
- Create a Python virtual environment named 'test' and activate it
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pip install virtualenv
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virtualenv test
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test\Scripts\activate
- Now, run the following command in your Terminal/Command Prompt to install the libraries required
- pip install -r requirements.txt
- Open terminal. Go into the cloned project directory and type the following command:
- python Password_app.py
- This project has tried with SVM, Logistic Regression and XGBoosting ML algorithms with 80000 amount of the data and among them SVM has selected as best performance algorithom interm of ROC values.
Logistic-Regreesion Confiusion Matrix: Open In Colab
- Among those model SVM has been selected because the SVM has a higher ROC-Value than the logistic regression model.