🚢 Titanic - Logistic Regression Classifier

A Kaggle notebook solution using Logistic Regression to predict survival on the Titanic. This project covers data exploration, preprocessing, model training, evaluation, and submission generation.

---

📚 Table of Contents

• 📌 Introduction
• 📦 Importing Required Libraries
• 📂 Data Loading and Exploration
  • 🔍 Train Dataset
  • 🔍 Test Dataset
  • 📊 Data Information
• 📈 Exploratory Data Analysis (EDA)
  • 🧩 Checking Missing Values
  • 🎨 Data Visualization
    • 🧮 Countplots
    • 📉 Histograms
    • 📦 Boxplots
• 🛠️ Feature Engineering
  • 🔧 Handling Missing Values
  • 🔁 Encoding Categorical Variables
  • 🎯 Feature Selection
• 🧪 Model Building
  • ✂️ Splitting the Data
  • 🧮 Logistic Regression Model
• 📏 Model Evaluation
  • ✅ Accuracy Score
  • 📉 Confusion Matrix
  • 🧾 Classification Report
  • 🧠 ROC Curve and AUC Score
• 🧾 Prediction on Test Data
• 📤 Submission File Creation
• 🏁 Conclusion

---

Feel free to explore each section above to understand the approach in detail!