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Expense Analysis Dashboard

The Expense Analysis Dashboard is a web application that enables users to upload spreadsheets of monthly expenses for automated analysis and visualization.
Using Python and Microsoft Azure services, the tool provides:

  • Detailed insights,
  • Trend analysis, and
  • Visual representations of financial data.

By leveraging machine learning models, this project empowers users to make informed budgeting decisions through accessible, data-driven dashboards.

Try it Now 🚀

Explore the live application:

Previously on Microsoft Azure:

The Expense Analysis Dashboard was also deployed in Microsoft Azure:
Expense Analysis Dashboard (Azure)

Update: Deployment in Azure has been removed due to charges being incurred on the account.

Skills and Learning

Data Analysis

  • Proficient in handling and analyzing spreadsheet data using Python libraries such as pandas and numpy.

Data Visualization

  • Created compelling visualizations using tools like plotly and matplotlib.
  • Applied visualization techniques to showcase insights from machine learning models.

Machine Learning

  • Trained machine learning models using scikit-learn to accurately predict future spending totals.
  • Built and optimized machine learning pipelines in Azure Machine Learning Studio, incorporating:
    • Data splitting,
    • Feature engineering,
    • Model training,
    • Evaluation, and
    • Scoring module integration.
  • Experienced in feature engineering and model evaluation to optimize predictions.

Azure Cloud Services

  • Configured Azure Blob Storage for efficient data management.
  • Designed and deployed an end-to-end machine learning pipeline in Azure.

Frontend Development

  • Designed interactive dashboards and applications using Streamlit.
  • Focused on creating intuitive user interfaces to visualize complex data.

Deployment

  • Successfully hosted applications on platforms such as Azure and Streamlit, ensuring accessibility and performance.