Alidzhon Aminov

Data Preprocessing with Numpy: Loan Dataset

In this project, I focused on preparing a loan dataset for analysis and machine learning using Python's NumPy library.

The key steps included:

• Cleaning: This involved solving missing or inconsistent data to ensure the dataset's reliability, a critical foundation for accurate machine learning predictions.
• Data Transformation: Transformed textual data into numerical values, enabling machine learning algorithms to effectively process and analyze the dataset.
• Dataset Optimization: The final step focused on refining the dataset by removing any redundant data and properly organizing the data. This ensured the dataset was clean, structured, and ready for machine learning applications.