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https://github.com/melling/titanicmachinelearning

A collection of different solutions to the Kaggle Titanic Competition.
https://github.com/melling/titanicmachinelearning

Last synced: 16 days ago
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A collection of different solutions to the Kaggle Titanic Competition.

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README

          

# Titanic Machine Learning

## R Language

### Logistic Regression

- https://github.com/Robby955/Titanic
- https://www.r-bloggers.com/2021/01/machine-learning-with-r-a-complete-guide-to-logistic-regression/

### Decision Trees

- https://www.r-bloggers.com/2016/02/titanic-machine-learning-from-disaster-part-1/

### Random Forest

- https://github.com/melling/TitanicMachineLearning/tree/main/solutions/wiekvoet/01_random_forest_wiekvoet
- https://github.com/melling/TitanicMachineLearning/tree/main/solutions/wiekvoet/04_random_forest_revisted_wiekvoet

### Bagging

- https://github.com/melling/TitanicMachineLearning/tree/main/solutions/wiekvoet/03_bagging_wiekvoet

### Deep Learning

- https://www.r-bloggers.com/2020/05/deep-learning-model-for-titanic-data/

### Bayesian

### Misc

- https://rstudio-pubs-static.s3.amazonaws.com/143316_106d643df86c4e4c8ae20e9775ab0ec7.html
- https://www.kaggle.com/pliptor/how-am-i-doing-with-my-score - Excellent Notebook with scores for dozens of solutions
- https://rpubs.com/JamesENelson/153826
- https://tylerburleigh.com/blog/surviving-the-titanic-with-r-caret/
- https://trevorstephens.com/kaggle-titanic-tutorial/getting-started-with-r/

## Python

- https://towardsdatascience.com/predicting-the-survival-of-titanic-passengers-30870ccc7e8
- https://github.com/MohammadWasil/Predicting-Titanic-Survivors
- https://humansofdata.atlan.com/2016/07/machine-learning-python/
- https://medium.com/better-programming/titanic-survival-prediction-using-machine-learning-4c5ff1e3fa16
- http://ghunt03.github.io/DAProjects/DAP02/TitanicDatasetInvestigation.html
- https://www.ritchieng.com/machine-learning-project-titanic-survival/
- https://www.kdnuggets.com/2016/07/titanic-machine-learning-guide-part-1.html
- https://youtu.be/fS70iptz-XU
- https://github.com/Arkham/jack-dies
- https://www.codementor.io/@innat_2k14/titanic-kaggle-machine-learning-from-disaster-part-1-10gbvqzguc
- http://www.caprinomics.com/projects/titanic/
- https://www.linkedin.com/pulse/how-i-scored-80-predicting-titanic-survivors-diogo-dutra
- https://www.geeksforgeeks.org/python-titanic-data-eda-using-seaborn/amp/
- https://pythonprogramming.net/k-means-titanic-dataset-machine-learning-tutorial/
- https://datascienceplus.com/logistic-regression-with-python-using-titanic-data/
- https://rstudio-pubs-static.s3.amazonaws.com/512981_db3552e79dc74dd0ada230125c27a4f3.html
- http://luizschiller.com/titanic/
- https://gearons.org/posts/titanic
- http://jasontdean.com/R/Titanic_Decision_Trees.html
- http://sajrest.com/Archives/vol4issue4_2019/v4i4p2.pdf
- http://www.owlnet.rice.edu/~ns10/Kaggle/pdfs/Titanic_Project.pdf
- http://mahanama94.me/surviving-titanic/
- http://vitarts.com.br/titanic-machine-learning-from-disaster-kaggle-copetitions/
- https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/5722190290795989/3865595167034368/8175309257345795/latest.html
- https://analyticsindiamag.com/solving-the-titanic-ml-survival-problem-using-random-forest-vs-neural-networks-on-tensorflow-which-one-is-better/
- http://jennhwang.me/blog/titanic/
- https://datascience.netlify.app/general/2017/07/20/data_science_9.html
- https://www.stefanfiott.com/data-science/titanic-survival-prediction/
- https://youtu.be/rODWw2_1mCI
- https://medium.com/better-programming/titanic-survival-prediction-using-machine-learning-4c5ff1e3fa16

## Misc

- https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/problem12.html

## Tidyverse

Analyze the Kaggle Titanic Data with the R Tidyverse

My attempt to learn Kaggle and R together.

I'm new to both Kaggle and R
R appears to be a great platform to investigate and learn about the data.

Having a computer science background, I'll probably use Python to build my models.

However, R with all its great libraries seems like the best place to start learning about the data. The EDA part.

Feel free to correct me on anything or offer suggestions.

```r
install.packages("tidyverse")
install.packages("randomForest")
install.packages("skimr")
install.packages("Prophet")
install.packages("forecast")
install.packages("scales")"

install.packages("tidymodels")

library('mice')
library(stringr)

```

## TidyVerse

https://www.tidyverse.org/

- [R for Data Science](https://r4ds.had.co.nz/)

## TidyModels

https://www.tidymodels.org/
=======
# Titanic in the Tidyverse

Analyze the Kaggle Titanic Data with the R Tidyverse.

This is an exercise to learn both the R/Tidyverse and Kaggle with the introduction Titanic competition.

## Misc Solutions

https://github.com/Robby955/Titanic/blob/master/titanic.R

## References

- https://www.kaggle.com/c/titanic
- https://github.com/Robby955/Titanic
- https://www.tidyverse.org

## R-Bloggers

- https://www.r-bloggers.com/2016/02/titanic-machine-learning-from-disaster-part-1/
- https://www.r-bloggers.com/2017/12/getting-started-with-dplyr-in-r-using-titanic-dataset/
- https://www.r-bloggers.com/2015/10/predicting-titanic-deaths-on-kaggle-vii-more-stan/
- https://www.r-bloggers.com/2018/08/understanding-titanic-dataset-with-h2os-automl-dalex-and-lares-library/
- https://www.r-bloggers.com/2018/01/understanding-naive-bayes-classifier-using-r/
- https://www.r-bloggers.com/2015/07/predicting-titanic-deaths-on-kaggle/