In this challenge, we'll build a predictive model that answers the question: “what sorts of people were more likely to survive to the Titanic tragedy?” using passenger data (name, age, gender, socio-economic class, etc).

Predicting Titanic survival using neural networks.

This repository contains the code for my attempt to solve the Kaggle Titanic Challenge.

Kaggle Titanic Comp

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 150.

this notebook is just a copy paste of other notebooks that I found online

Titanic spaceship is a simple challenge of kaggle competitions. Task is to predict whether a passenger was transported to an alternate dimension during the Spaceship Titanic's collision with the spacetime anomaly. I could to get 0.802 accuracy.

DataScience projects for learning : Kaggle challenges,

The main purpose of this repo is to understand the approach towards EDA.

Titanic Survival Prediction: Jupyter Notebook demonstrating Random Forest Classifier for survival prediction on Titanic dataset.

This repository contains my internship tasks for the company Prodigy-InfoTech.

Repositório com a minha participação na competição do Kaggle

Repositório com a minha participação na competição do Kaggle

This is a repository for Titanic dataset analysis with EDA notebook and Power BI dashboard.

Use the popular titanic dataset from Kaggle with DVC to test and deploy an ML pipeline

🚢 Association and Pattern Recognition Algorithms on data from Titanic survivors.

Titanic survival analysis using Decision tree

This is my first Machine Learning Project. The project employs a variety of machine learning models, including Random Forests, Gradient Boosted Trees, and Neural Networks, to predict survival. Techniques for data cleaning, feature engineering, and model tuning are thoroughly documented in the Jupyter notebooks.