Titanic Survival prediction: Titanic dataset- how many people survive and how many were Male and Female
Deep learning (TabFormer) experiment for the Kaggle Titanic ML competition - binary survival prediction.
Predict who is likely to have survived in the titanic crash given his/her information
Start here! Predict survival on the Titanic and get familiar with ML basics.This is the legendary Titanic ML competition – the best, first challenge for you to dive into ML competitions and familiarize yourself with how the Kaggle platform works.
This project aims to predict the survival of passengers aboard the Titanic using the Naive Bayes classifier algorithm. The dataset used in this project contains information about Titanic passengers, such as their age, gender, passenger class, and other relevant features.
End-to-end Machine Learning pipeline with Streamlit deployment to predict Titanic passenger survival.
AI/ML project predicting Titanic passenger survival using feature engineering, preprocessing, and classification models with Python and scikit-learn.
How to perform an exploratory data analysis on the Kaggle Titanic dataset.
This project uses the famous Titanic dataset to predict passenger survival in the 1912 disaster. By applying machine learning classification techniques, the model learns from features to determine whether a passenger survived or not.
End-to-end ML classification on the Titanic dataset: EDA, feature engineering, Logistic Regression & Random Forest, cross-validation, hyperparameter tuning
Data analysis and Machine learning on titanic data
A data-driven analysis and machine learning model to predict passenger survival in the Titanic disaster using Python, Pandas, and Scikit-learn.
Predicting Titanic passenger survival using Machine Learning (Gradient Boosting) in Python.
The goal of this project is predicting the survival of passengers based on a set of data. Necessary data is retrieved from Kaggle competition "Titanic: Machine Learning from Disaster".
TOP13% solution for the Titanic-Kaggle competition using a Gradient Boosting Classifier. Moreover, implementation of a Streamlit App to play with the models.
Data Science internship at Asterisc Technocrat Pvt. Ltd. Task - Billioniaire Analysis, Covid - 19 Data Analysis, Titanic Survival Prediction
A high-performance Python framework to generate and validate 100,000 synthetic passenger records across 31 features for modern tabular ML benchmarks, risk modeling, and binary classification.
Titanic Survival Prediction Project (Data Science) || Tech Stack: Python, Pandas, Numpy, Matplotlib, Seaborn, Scikit-Learn
Kaggle Machine Learning Competition
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