Update app.py

app.py

@@ -48,9 +48,9 @@ with Conclusion:
   st.write("The presence of 55 unmatched predictions in the RFC model indicates the need for further analysis and improvement. By addressing data quality issues, optimizing hyperparameters, considering feature engineering, and exploring ensemble methods, the model's performance can be enhanced. Regular evaluation and monitoring will ensure that the model remains effective in predicting loan approvals and supports the lending institution's decision-making process.")  
 
 with Home:
-  st.title("Milestone 2 - Create Model Loan Prediction")
-  st.subheader("Problem Statement")
-  st.write('Develop a robust machine learning model for loan prediction that accurately classifies loan applications as either approved or rejected, while also segmenting the approved loans into three risk categories: low risk, moderate risk, and high risk. The model should leverage historical loan data, applicant information, and credit analysis to make informed decisions, enabling the lending institution to streamline the loan approval process and mitigate potential credit risks effectively.')
+  st.title("Final Project - Uncover potential insights 1999 Czech Bank Financial Dataset ")
+  st.subheader("Abstract")
+  st.write('This study presents an exploratory analysis of banking data to uncover potential insights and patterns related to customer behavior, credit risk assessment, geographic influences, customer segmentations, and time series trends. The analysis is conducted by integrating multiple tables containing transaction records, customer demographics, and district characteristics. The study employs various analytical techniques to extract valuable information from the data.')
   st.image('loan.jpg')
   bisnis = st.container()
   with bisnis: