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A classification approach to the machine learning Titanic survival challenge on Kaggle.Data visualisation, data preprocessing and different algorithms are tested and explained in form of Jupyter Notebooks
10 very popular data analysis exercises I have practised with jupyter notebook in my spare time, including Iris flowers, Titanic, K means clustering, linnear regression and logistic regression etc.
The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of thi…
In this notebook, we will work on the Titanic dataset and use machine learning to create a model that predicts which passengers survived the Titanic shipwreck.
Titanic Survival Prediction Project (93% Accuracy)🛳️ In this notebook, The goal is to correctly predict if someone survived the Titanic shipwreck using different Machine Learning Model & Hyperparameter tunning.
This is my first Machine Learning Project. The project employs a variety of machine learning models, including Random Forests, Gradient Boosted Trees, and Neural Networks, to predict survival. Techniques for data cleaning, feature engineering, and model tuning are thoroughly documented in the Jupyter notebooks.