Prediction model for kaggle's Titanic survival prediction machine learning competition (over 80% accuracy)
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Updated
Dec 9, 2019 - HTML
Prediction model for kaggle's Titanic survival prediction machine learning competition (over 80% accuracy)
Titanic Survival Exploration with NumPy, Pandas and Scikit-Learn
final project on titanic dataset in nanodegree program of udacity
Welcome to the Titanic Survival Prediction Project! This website is a detailed showcase of my machine learning journey with the Titanic dataset from Kaggle. Through this project, I've explored various machine learning models and techniques to predict the survival of passengers aboard the Titanic.
Kaggle competition project.
Which types of people were more likely to survive the Titanic Disaster?
Machine Learning Pipeline, to engineer the features in the dataset and predict who is more likely to survive the catastrophe.
Ever wondered what would happen if you were onboard the Titanic? Would you survive or would you die? This project serves to answer this- We use the Kaggle Titanic dataset to build an ML model in Python. We then use a Flask API to deploy the model to Heroku app; where you can simply answer 7 questions and find out whether you survive or DIE!
Predict the survival of Titanic passenger
A binary classification model, inspired by the "Titanic" Kaggle Challenge. Predicts whether or not a given passenger will survive, based on personal characteristics such as age, gender, and how much money their ticket cost.
This repository includes a Python supervised classification project on Titanic in HTML as well as in Jupyter Notebook form, and it also includes PowerBI file for EDA of Titanic Dataset.
This repository provides a complete solution to Udacity's Machine Learning Project "Titanic_Survival_Exploration".
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