I have tried to Engineer some features of training and test dataset.

This 2018 Developer Survey results are organized on Kaggle in two tables and Telecom churn dataset on Kaggle, objective was EDA

Dataset: NYC Property Sales (kaggle). indo tutorial by indosoai https://www.youtube.com/watch?v=1jzvGdIB9bo

Predicting an tweet is positive or negative using Logistic Regression

Participating in Google Landmark Recognition 2019 ( https://www.kaggle.com/c/landmark-recognition-2019/overview )

The Competition is present on Kaggel

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.

Analyze gapminder data and unveil the relationships between multiple variables

Analyze No-show appointments data and unveil the relationships between multiple variables

Analyze TMDb movie data and unveil the relationships between multiple variables

Analyze soccerr data and unveil the relationships between multiple variables

Analyze FBI gun data and unveil the relationships between multiple variables

This repository consists of the Analysis and ML training of the MNIST_Digit_recognizer on kaggle

This is our second project at neuefische DS Bootcamp. Silas Mederer (https://github.com/sls-mdr) and me applied different ML models and for credit default prediction of the P2P platform Lending Club.

This repository contains code how to build job recommendation engine using Kaggle 'Job Recommendation Challenge' dataset

Add dynamically generated Kaggle Tier & Medals on your readme.