Welcome to the Data Science Hub repository! This is a collection of personal projects and notebooks that I've worked on to enhance my skills and knowledge in the field of data science. Each notebook represents a different project, showcasing various techniques and methodologies applied to real-world problems.
This project involves predicting employee attrition using classification algorithms. The notebook demonstrates how to preprocess data, build models, and evaluate their performance to predict which employees are at risk of leaving the company.
In this notebook, I explore multi-level models to predict obesity levels based on various features. The project includes data cleaning, feature selection, and model evaluation, providing insights into factors contributing to obesity.
This project focuses on predicting customer churn using various machine learning algorithms. The notebook includes steps for data exploration, feature engineering, model training, and evaluation to identify customers who are likely to churn.
Stay tuned for more exciting projects and updates as I continue to explore and work on new data science challenges!
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Clone the repository to your local machine:
git clone https://github.com/adarshadda/Data-science-Hub.git
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Navigate to the directory containing the notebooks:
cd Data-science-Hub -
Open the desired notebook using Jupyter or any other notebook viewer:
jupyter notebook <notebook_name>.ipynb
- Python
- Jupyter Notebook
- Pandas
- NumPy
- Scikit-learn
- Matplotlib
- Seaborn
- more..
However, this is a personal project repository, contributions are also accepted to so if you have suggestions or improvements, feel free to open an issue or contact me.
If you have any questions or would like to discuss the projects, feel free to reach out to me at [[email protected]].
Thank you for visiting my Data Science Hub! I hope you find these projects insightful and inspiring.