There are 2 repositories under kaggle-titanic topic.
A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.
Solution of the Titanic Kaggle competition
Kaggle Titanic example
Titanic assignment on Kaggle competition
Training models with Apache Spark, PySpark for Titanic Kaggle competition
Detailed notes and code to learn machine learning with Apache Spark.
All my Kaggle Notebooks that I've published
The concepts of DS and ML, written by me ;)
Analyse the Titanic Data Set from Kaggle and predict a classification- survival or deceased
https://towardsdatascience.com/a-beginners-guide-to-kaggle-s-titanic-problem-3193cb56f6ca
The most famous competition over the kaggle .
This Repository Contains all my Machine Learning Projects that I have mad for, Competitions that I have Participated or tried for Practice.
Important books, cheat sheet, notebooks for machine learning.
Trying out things on Kaggle's Titanic dataset
Data playground for improving machine learning skills using Kaggle datasets. Work in Progress: Listed here are Kaggle competitions I am working on, not necessarily finished.
:jack_o_lantern:Kaggle-Comptetion-Titanic-Dataset(Codeperfectplus):trophy:
A Keras/TensorFlow + XGBoost ensemble Neural Network stack.
Spaceship Titanic Kaggle Challenge - Includes detailed EDA and statistical analysis, NaN-Imputation and Modeling. (> 80% accuracy, top 6% on 09.08.22)
My Data Mining Training Repository
Here is a small collection of how to use MATLAB to solve Machine Learning challenges
hand code for application and software design practice
This repo contains the solutions of the assignments of the courses and submissions in the competitions with dataset required, which were part of 30 Days of ML by Kaggle.
Cleaning data and building a classification algorithm for Kaggle's Spaceship Titanic competition. (Accuracy = 80.5)
Classification model on Titanic: Tragic shipwreck with EDA. Secured Accuracy Score of ~0.78.
Project made in Jupyter Notebook with Kaggle Titanic dataset, which aims at detailed data analysis and prediction of which passengers survived the sinking of the Titanic.
This a live workshop on "How to Join kaggle compitetion hands-on"
Kaggle Titanic Prediction problem solved using Python
A comparison between Linfa algorithms for titanic dataset.
Getting to top 4% on Kaggle's Titanic using Azure Automated Machine Learning
Competitions, Datasets, Notebooks
Titanic - Machine Learning from Disaster