Ecosyste.ms: Repos
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GitHub topics: titanic-data
yugoff/ml-kaggle-forecast-of-survival-on-the-Titanic
Language: Jupyter Notebook - Size: 141 KB - Last synced: 3 months ago - Pushed: 7 months ago - Stars: 0 - Forks: 0
ashishpatel26/Titanic-Machine-Learning-from-Disaster
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
Language: Jupyter Notebook - Size: 224 KB - Last synced: 8 months ago - Pushed: over 1 year ago - Stars: 45 - Forks: 69
SoundaryaMiranam/Survival_prediction_Titanic-disaster
Data analysis and Machine learning on titanic data
Language: Python - Size: 44.9 KB - Last synced: about 1 year ago - Pushed: about 3 years ago - Stars: 0 - Forks: 0
saheelahmed2/Titanic-EDA
Exploratory Data Analysis on Titanic Survivor Dataset provided by Kaggle.
Language: Jupyter Notebook - Size: 506 KB - Last synced: about 1 year ago - Pushed: almost 6 years ago - Stars: 1 - Forks: 1
deep-diver/Data-Analysis-on-Titanic
applying data analysis on titanic data sheet
Language: Jupyter Notebook - Size: 482 KB - Last synced: about 1 month ago - Pushed: over 6 years ago - Stars: 2 - Forks: 1
