In this project we are going to perform exploartory data analysis and ccreate machine learning models using following algorithms:
- Logistic regression
- SVM
- MLP
- RF
- Gradient Boosting
to predict the species of a given penguin.
The Penguin dataset contains following attributes:
- species: penguin species (Chinstrap, Adélie, or Gentoo)
- culmen_length_mm: culmen length (mm)
- culmen_depth_mm: culmen depth (mm)
- flipper_length_mm: flipper length (mm)
- body_mass_g: body mass (g)
- island: island name (Dream, Torgersen, or Biscoe) in the Palmer Archipelago (Antarctica)
- sex: penguin sex
The target attribute: species
To develop this project Jupyter Notebooks and Anaconda are used. You can install Anaconda from here. Then either use Jupyter Labs or jupyter notebook extension to open the files. You can also view the project on Kaggle here
Data were collected and made available by Dr. Kristen Gorman and the Palmer Station, Antarctica LTER, a member of the Long Term Ecological Research Network. License & citation • Data are available by CC-0 license in accordance with the Palmer Station LTER Data Policy and the LTER Data Access Policy for Type I data. • Please cite this data using: Gorman KB, Williams TD, Fraser WR (2014) Ecological Sexual Dimorphism and Environmental Variability within a Community of Antarctic Penguins (Genus Pygoscelis). PLoS ONE 9(3): e90081. doi:10.1371/journal.pone.0090081 citation
CC-0 license