This project predicts Titanic survival using a Random Forest classifier and a Django web interface for user inputs (family, fare, class, etc.). It combines machine learning and web development for real-time predictions.

Codes for Kaggle Competitions

A modernized adaptation of the Coursera guided project. Replaces some of the old packages and commands.

My prediction solution for the Kaggle Titanic competition. I used Snowflake ML Classification model.

Survival prediction based on the Kaggle competition: "Titanic - Machine Learning from Disaster".

Kaggle Titanic ML competition. Top 2% score.

All my Kaggle Notebooks that I've published

Este projeto analisa o conjunto de dados do Titanic para prever a sobrevivência dos passageiros usando modelos de aprendizado de máquina. O projeto inclui pré-processamento de dados, engenharia de recursos, treinamento de modelo e avaliação.

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.

Predict survival on the Titanic and get familiar with ML basics

Discover Kaggle competitions code, notebooks, and datasets. Enhance your data skills, learn from real-world challenges, and find inspiration in this learning repository for beginners.

Following along with Ken Jee's tutorial for beginner Kaggle competition

Titanic - Machine Learning from Disaster (Kaggle Competition)

Data science projects, classification, clustering, visualization

Titanic - Machine Learning from Disaster. kaggle competition

Hello ! 👋 I'm thrilled to share my debut in the world of Kaggle competitions with my solution for the Titanic: Machine Learning from Disaster competition. In this challenge, we are tasked with predicting which passengers were more likely to survive the tragic sinking of the Titanic. Public Score: 0.79186

Predicting the mileage of car using the linear regression model with Scikit-learn