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.

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Try it Now 🚀

Explore the live application:

• YouTube
• Expense Analysis Dashboard (Streamlit)

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.

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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.