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

Kaggle入门级机器学习项目：泰坦尼克号生存预测

Using Machine learning algorithm on the famous Titanic Disaster Dataset for Predicting the survival of the passenger.

Applying Machine Learning Algorithms to the Kaggle "Titanic Survival Prediction Problem".

API взаимодействие с моделью

Titanic Survival prediction: Titanic dataset- how many people survive and how many were Male and Female

Experiments in ML with tidymodels

Titanic rescue prediction using Decision Tree, SVM, Logistic Regression, Random Forest and KNN. The best accuracy score was from Random Forest: 84.35%

Introductory Kaggle competition

kaggle machine learning with spark

Predict if you would have survived if you were on the Titanic Ship

Testing different ML models on famous Titanic dataset from kaggle. (100% accuracy)

This is collection of My Data Analysis and Python Leaning

My Solutions to Machine Learning competitions on Kaggle, Analytics Vidhya etc

This is my personal repository, I upload my personal projects here. You can copy the code without a second thought. Thank you

Data Analysis Solution for Titanic passenger data.

My take on the Kaggle Titanic Challenge, Accuracy: 0.80681

Predicting the survival of passengers on RMS Titanic using information about the passengers.

EDA,Feature Engineering and Modelling for classical Titanic Problem

Machine learning models for predicting Titanic survival. Includes data preprocessing, model training, and performance comparison using various algorithms. Features a Random Forest model with the highest ROC AUC for accurate predictions.

Learn Logistic Regression and implement by Java， also used to solve Kaggle-Titanic predict。

This Repo holds the projects, which I completed as part Udacity Data Analyst Nano Degree. 👨‍🎓🤘

Ames Housing price Prediction, SAT_ACT statistical analysis,Reddit engagement using natural Language processing TF-IDF, Titanic survival predictions

Using Machine learning algorithm on the famous Titanic Disaster Dataset

Titanic kaggle comp, Spam Ham (Regressors and classifiers)

DataScience projects for learning : Kaggle challenges,

Prediction survival on the Titanic using Logistic Regression

A Machine Learning Model based on Logistic Regression that predicts the survival of passengers travelled in Titanic.

XGBoost classification model predicting Titanic passenger survival with data preprocessing, feature engineering, and SMOTE for class balancing. Developed for the Kaggle Titanic competition.

Hello friends, I am making a Machine Learning repo. where I will upload several datasets and its solution with explanation. Starting from the basic and moving up in difficulty level.