Welcome to my Data Science repository! This project serves as a comprehensive portfolio of my work, documenting my journey through data analysis, visualization, and machine learning.
| Folder / File | Description |
|---|---|
Capestone Project |
The final project involving end-to-end data science methodology: data collection, wrangling, EDA, and predictive modeling. |
Data Analysis w\Python |
Focuses on data cleaning, wrangling, and exploratory statistical analysis using Pandas and Numpy. |
Data Visualization |
Contains scripts and notebooks for visual storytelling using Matplotlib, Seaborn, and interactive web-app components. |
Machine Learning w\Python |
Implementation of machine learning models including Regression, Classification, and Clustering using Scikit-learn. |
DataScienceEcosystem.ipynb |
An overview of the data science landscape, including essential libraries, open-source tools, and development environments. |
- Language: Python
- Data Libraries: Pandas, NumPy, SciPy
- Visualization: Matplotlib, Seaborn, Plotly, Dash
- Machine Learning: Scikit-learn
- Environment: Jupyter Notebooks, GitHub
- Model Refinement: Fine-tuning predictive models for pricing analysis (e.g., Laptop and Automobile pricing).
- Interactive Dashboards: Creating paths for historical trend analysis via web applications.
- Statistical Modeling: Applying rigorous data analysis techniques to derive actionable insights from raw data.
Dhyandave28
- Passionate about turning data into insights.
Last updated: February 2026