Titanic - ML Project
Titanic - ML Project
This will be the first dataset everyone starts for kaggle competitions. The dataset is easy to interpret and can start with the basic libraries like numpy, pandas, seaborn and matplotlib in Python. The objective is to predict whether a passenger in titanic survived or not survived based on the features or predictor variables.
In KNIME Analytics Platform, we can do this ML project without coding or without using python. Everything from EDA, Data Cleaning, Normalization, Variable encoding, Data Partioning, Model Building & Sample File submission is covered. More can be done but this project is aimed for beginners.
Download KNIME and this workflow from my KNIME hub.
URL: Titanic ML Competition - Predict Survival https://www.kaggle.com/augustinej/beginner-s-kaggle-ml-competition-titanic
URL: LinkedIn https://www.linkedin.com/in/augustine-joseph
Nodes
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Ensemble Learning Wrappers
- FeatureKNIME JavaScript Views
- FeatureKNIME JavaScript Views (Labs)
- FeatureKNIME JFreeChart
- FeatureKNIME Reporting Runtime (BIRT)
- FeatureKNIME Statistics Nodes
- FeatureKNIME XGBoost Integration
Links
- No links available