"Would YOU Survive the Titanic?", with ML and .NET
summary
Uses Visual Studio and C# with ML.NET to train on the Kaggle Titanic CSV, showing a concrete pipeline: clean missing ages, drop cabins, extract titles and decks, one‑hot encode, then run ML.NET AutoML and manual trainers to compare. Models compile into C# files and run fast; baseline scores hit about 77.8% accuracy and a manual FastForest variant reaches ~78.9%. Demonstrates a hosted web app that predicts survival, shows the exact data fixes and training times used.
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chapters (8)
- 0:00Titanic survival challenge
- 3:13What is machine learning
- 10:14Analyzing Titanic data
- 16:13Building model with ML.NET
- 22:14Refining predictions
- 25:47ML pipeline in .NET
- 30:21Live survival prediction
- 37:43Wrap-up and resources
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