Python Projects
Python Projects
Insurance Data Analysis Using Python
Features :
Data Preparation: Collected and cleaned insurance datasets.
Exploratory Analysis: Analyzed data distributions, correlations, and patterns.
Claims Analysis: Identified common claim types and frequencies.
Customer Segmentation: Segmented customers based on demographics and claim history.
Risk Assessment: Evaluated risk factors affecting premiums and claims.
Predictive Modeling: Built models to forecast claims and customer behavior.
Fraud Detection: Implemented techniques to detect potential fraud.
Visualizations: Created visualizations with Matplotlib and Seaborn.
Reporting: Generated reports with key insights and recommendations.
Skills: Data Collection and Cleaning , Data Visualization , Python Programming , Problem Solving ·,Statistical Analysis
Features :
Analyzing an app rating dataset and making prediction for future app based on parameters available in dataset.
• Data Preparation and Exploration
• Data Cleaning and Formatting
• Data Preprocessing for Modeling
• Data Integrity Checks and Sanity Validation
• Model Building and Evaluation
• Outlier Treatment and Data Adjustment
• Tech-stack : Jupyter Notebook, NumPy, Pandas, Matplotlib or Seaborn (for data visualization).
Skills: Data Collection and Cleaning ,Data Visualization ,Python Programming ,Problem Solving ,Statistical Analysis