#Data Science Python

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1. Customer Churn Prediction -Business Aspect: Retain customers, reduce churn rate, increase CLV (Customer Lifetime Value). -Tech Used: Python, Scikit-learn, XGBoost, Pandas, SQL, Flask/FastAPI (deployment), AWS Sagemaker / GCP AI Platform, Power BI/Tableau (dashboards). 2. Dynamic Pricing System -Business Aspect: Optimize product/service pricing for revenue maximization. -Tech Used: Python, TensorFlow/PyTorch, Scikit-learn, Airflow (pipeline), PostgreSQL, Docker, Kubernetes, Streamlit dashboard. 3. Fraud Detection in Transactions -Business Aspect: Reduce financial loss and risk in banking/fintech. -Tech Used: Python, PyTorch/LightGBM, Kafka (real-time streaming), Spark MLlib, AWS Kinesis, Flask API, Grafana monitoring. 4. Demand Forecasting for Retail -Business Aspect: Inventory optimization, supply chain efficiency. -Tech Used: Python, Prophet/ARIMA/LSTM, Pandas, SQL, Airflow, GCP BigQuery, Looker/Tableau for visualization. 5. Personalized Recommendation System -Business Aspect: Boost sales, engagement, and cross-selling. -Tech Used: Python, PyTorch/TensorFlow, Scikit-learn, Neo4j (graph-based recsys), Redis (caching), Flask/FastAPI, AWS Lambda. 6. Predictive Maintenance for Manufacturing -Business Aspect: Reduce downtime and maintenance costs. -Tech Used: Python, Scikit-learn, PyTorch (time-series modeling), IoT data ingestion with Kafka, Spark, Azure ML, Grafana. 7. Credit Risk Scoring -Business Aspect: Approve/deny loans more effectively, reduce default risk. -Tech Used: Python, Scikit-learn, XGBoost, SHAP (explainability), SQL, Airflow, Flask API, Streamlit dashboard. 8. Marketing Campaign Response Prediction -Business Aspect: Optimize ad spend, improve conversion rates. -Tech Used: Python, Scikit-learn, LightGBM, AWS Redshift, Airflow, Power BI/Tableau. #datascience #machinelearning #womeninstem #learningtogether #progresseveryday #tech #consistency