This Jupyter Notebook details the analysis of the famous Kaggle dataset entitled "Titanic: Machine Learning from Disaster" using various data visualisation models and analysis using Machine Learning.
I provide an indepth analysis detailing my processes of converting the data into meaningful insights describing the differences and distributions in class, gender, age, fare cost etc. Finally, I predict the likelihood that a passenger survived with machine learning by analysing their age, socioeconomic status and other variables.
My analysis uses the following modules (packages):
- Seaborn
- Matplotlib
- Numpy
- Pandas
- RegEx
- Machine Learning (sklearn)