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Notebook
I shared my Colab notebook so you can follow along line-by-line without getting stuck on setup. It includes the full pipeline I used: missing value handling, feature engineering (Title, FamilySize, IsAlone), one-hot encoding, model training, and submission file creation.
Pros
- +Ready-to-run code for the full Titanic solution workflow
- +Helps you reproduce submissions quickly and experiment with parameters
- +Good reference structure for future ML projects
Cons
- -You’ll still need to tweak hyperparameters yourself to explore improvements
- -Notebook assumes basic familiarity with pandas and scikit-learn
What Sreemanti Dey says
“So you download the data, build the models locally or on Kaggle notebooks”
“And let's make a new notebook there”
“Next we going to just uh u notebook sounds good”
“So basically you know you have the notebook you have everything just change this to six change this to 10 change this to 11 and then try out like try out your by yourself to see what exactly the sports that you get”
Featured in this video
Notebook
Available on Colab
External purchase
Highlights
- +Ready-to-run code for the full Titanic solution workflow
- +Helps you reproduce submissions quickly and experiment with parameters
- +Good reference structure for future ML projects
Recommended by
Sreemanti Dey