Welcome to the CognoRise Infotech internship projects repository. This repository contains the data analysis projects I completed as part of the internship program.
- Description: An analysis of the nutritional content of 80 different cereals to determine their health ratings. This project aims to identify trends and provide insights for healthier consumer choices.
- Technologies Used: Python, Pandas, Matplotlib, Seaborn
- Files:
80_cereals_analysis.ipynb: Jupyter notebook with code and analysis.cereal_data.csv: Dataset used for analysis.
- Description: A machine learning project that evaluates factors affecting the quality of red wine. The project involves predicting wine quality based on various features.
- Technologies Used: Python, Scikit-learn, Pandas, Seaborn, Matplotlib
- Files:
red_wine_quality.ipynb: Jupyter notebook with code and model implementation.winequality-red.csv: Dataset used for model training and analysis.
- Description: A data analysis project focused on unemployment trends in India. The project explores historical data to uncover patterns and suggests potential solutions for reducing unemployment.
- Technologies Used: Python, Pandas, Matplotlib, Seaborn
- Files:
unemployment_analysis.ipynb: Jupyter notebook with code and analysis.unemployment_data.csv: Dataset used for analysis.
To get started with these projects, clone the repository and open the respective Jupyter notebooks.
git clone https://github.com/yourusername/CognoRise-Infotech.git
cd CognoRise-InfotechEnsure you have the following dependencies installed:
- Python 3.x
- Jupyter Notebook
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn (for Red Wine Quality project)
You can install the dependencies using pip:
pip install pandas matplotlib seaborn scikit-learn- Open the Jupyter notebook for the project you want to explore.
- Run the cells in the notebook to reproduce the analysis and results.