This is the first of a three part series of tutorials on how to use KNIME for a Kaggle machine learning problem. This tutorial is a beginner friendly way to build a machine learning model without needing to write code.
The Titanic problem is a classification problem that is a classic from Kaggle where data scientists try to use some passenger data to predict who survived and who did not.
Kaggle problem and data here: https://www.kaggle.com/c/titanic
Download KNIME here: https://www.knime.com/downloads
In this tutorial we will cover data cleaning and preparation. We will utilize a random forest model to make our predictions. And finally, we will utilize feature engineering to improve our model's performance.
Please look for parts 2 and 3 of the tutorial coming soon.
