Titanic Kaggle Data Science Project - Beginners Walkthrough Code Along with Me

🚢 Predict Titanic Survival with Machine Learning | Full Kaggle Walkthrough (Python + Sklearn)

In this video, we walk through a complete machine learning project using the Titanic dataset from Kaggle. From exploring the data to building predictive models and generating a submission file — this is everything you need to get started with real-world data science in Python.

📘 What You’ll Learn:

- How to load and explore real datasets
- Handling missing data and null value inspection
- Feature engineering (e.g., extracting titles from names)
- Encoding categorical variables
- Building and evaluating models (Logistic Regression + Random Forest)
- Visualizing feature importance
- Creating a Kaggle-ready submission file
🔗 Resources: 👉 Kaggle Titanic Competition: https://www.kaggle.com/competitions/titanic
👉 GitHub Repo: https://github.com/madams239/titanic/blob/main/README.md
👉 Notebook & Code: Included in the GitHub repo
👉 Requirements.txt: Included for easy setup

📈 Whether you're a beginner looking to build your first machine learning model, or prepping for data science interviews, this project is a must-have in your portfolio.

Chapters: 0:00 - Intro
1:15 - Environment Setup
10:30 - Exploratory Data Analysis
20:13 - Feature Engineering
33:30 - Training Models
36:04 - Model Evaluation + Random Forest Model
42:04 - Cross Validation
👍 If you found this helpful, don’t forget to like, subscribe, and drop a comment letting me know what project you’d like to see next!
43:24 - Closing

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Видео Titanic Kaggle Data Science Project - Beginners Walkthrough Code Along with Me канала Data Guy Michael