Скачать или смотреть Build a Customer Churn Prediction System with Machine Learning | Python Project Tutorial

Build a professional Customer Churn Prediction System from scratch using Python, Machine Learning, and Streamlit! 🚀

In this comprehensive tutorial, you'll learn:
✅ Data cleaning and preprocessing techniques
✅ Exploratory Data Analysis (EDA) with visualizations
✅ Handling imbalanced datasets using SMOTE
✅ Training and comparing multiple ML models (Decision Tree, Random Forest, XGBoost)
✅ Model evaluation with confusion matrix and metrics
✅ Saving and loading trained models
✅ Building an interactive Streamlit web application
✅ Extracting actionable business insights

📊 WHAT YOU'LL BUILD:
A complete churn prediction system that achieves 78% accuracy using Random Forest, with a beautiful web interface for real-time predictions.

🎯 WHO THIS IS FOR:
Data Science beginners to intermediate learners
Students building ML portfolios
Anyone preparing for data science interviews
Business analysts wanting to learn ML

📦 DATASET:
Telco Customer Churn Dataset - 7,043 customers with 20+ features

🛠️ TECHNOLOGIES:
Python 3.10+
Pandas & NumPy
Scikit-learn
Imbalanced-learn (SMOTE)
XGBoost
Matplotlib & Seaborn
Streamlit
Plotly

📁 RESOURCES:
🔗 Complete Code: [ https://github.com/TensorTitans01/Cus... ]

💼 REAL-WORLD APPLICATION:
This project demonstrates skills directly applicable to jobs in:
Data Science
Machine Learning Engineering
Business Analytics
Customer Success Analytics
Marketing Analytics

🎓 WHAT YOU'LL LEARN:
1. How to handle messy real-world data
2. Dealing with class imbalance using SMOTE
3. Feature importance analysis
4. Model comparison techniques
5. Production-ready model deployment
6. Translating ML results into business insights

📈 KEY RESULTS:
78% accuracy on test data
59% recall for churn detection
Top features: Contract type, Tenure, Monthly charges
Deployed with interactive UI

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📚 RELATED VIDEOS:
[    • Machine Learning Projects   ]

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🏷️ TAGS:
#MachineLearning #Python #DataScience #ChurnPrediction #StreamlitApp #MLProject #PythonTutorial #RandomForest #DataAnalytics #PortfolioProject

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📧 BUSINESS INQUIRIES: [ [email protected]]
🐦 INSTAGRAM : [   / tensortitans   ]
🐙 GITHUB: [ https://github.com/TensorTitans01 ]

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⚖️ DISCLAIMER:
This tutorial is for educational purposes. The dataset is publicly available for learning.

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