a supervised machine learning model that detects malicious login attempts using the Attack IP field from the Risk-Based Authentication (RBA) dataset as the target
This repository contains a Jupyter Notebook titled ML_Model_Malicious_Login.ipynb, which represents the fourth milestone of a group machine learning project.
This notebook includes:
- Data preprocessing and cleaning
- Model selection and training
- Performance evaluation using appropriate metrics
- Interpretations and conclusions based on results
The goal of this project is to develop a machine learning model capable of solving a specific problem using appropriate techniques.
- Python
- Jupyter Notebook
- Pandas, NumPy
- Scikit-learn
- Matplotlib and Seaborn
- Trains one or more ML models on a dataset
- Compares performance between models
- Visualizes important metrics or results
- Concludes with an analysis of model performance
To run the notebook:
- Clone the repository:
git clone https://https://github.com/Devanshi678/ML_Model_RBA.git cd ML_Model_RBA
- Make sure all required libraries are installed before running the notebook.
- recommend using a virtual environment