There are 3 repositories under titanic-survival-prediction topic.
Start here if... You're new to data science and machine learning, or looking for a simple intro to the Kaggle prediction competitions. Competition Description The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy. Practice Skills Binary classification Python and R basics
Infamous Titanic survial prediction competition on Kaggle
Using Machine learning algorithm on the famous Titanic Disaster Dataset for Predicting the survival of the passenger.
A demo of vertical federated learning on simple datasets
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
This program consists of clean and polished Graphical User Interface (GUI) that interacts with 8 Machine Learning models and data visualization tools through the use of different Python libraries. The user can interact with the GUI through selecting which model to run on the testing data on, which then takes them to a screen displaying the prediction results of the testing data as well as the general model accuracy. The screen also includes various buttons that, when selected, display complex and attractive data visualizations on the testing data.
Applying Machine Learning Algorithms to the Kaggle "Titanic Survival Prediction Problem".
Titanic Survival prediction: Titanic dataset- how many people survive and how many were Male and Female
API-First approach to make Machine Learning solution usable
A machine learning model to predict the survivors
My take on the Kaggle Titanic Challenge, Accuracy: 0.80681
Testing different ML models on famous Titanic dataset from kaggle. (100% accuracy)
Some useful examples of Deep Learning (.ipynb)
Predicting the survival of passengers on RMS Titanic using information about the passengers.
Using Machine learning algorithm on the famous Titanic Disaster Dataset
A Machine Learning Model based on Logistic Regression that predicts the survival of passengers travelled in Titanic.
: Visualization & Prediction
Welcome to the Titanic Classification project repository! This project aims to predict whether a passenger on the Titanic survived or not based on various features such as age, gender, class, and more.
Prediction survival on the Titanic using Logistic Regression
My implementation for Logistic Regression and applying it to different data sets.
Titanic Survivor Prediction
Classification model on Titanic: Tragic shipwreck with EDA. Secured Accuracy Score of ~0.78.
This was my first step into machine learning, Its not new, I am just uploading it on Github now. Its a llinear regression model
Very basic data exploration of the Titanic Dataset.
A small machine learning project.
This repo contains all of my submissions to Kaggle competitions or datasets
Machine Learning from Titanic Disaster
Deploying the Titanic survival prediction ML problem using flask
Titanic Survival Prediction using Logistic Regression
A machine learning model to predict the survived passengers from the titanic disaster.
This notebook contains my submission of Titanic submission challenge on Kaggle. Feel free to suggest improvements.
Titanic Survival Prediction Using Machine Learning
Process of Data Analysis of the famous Titanic dataset with Predict Model of survival
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.