Using Classification algorithms to predict whether a candidate will apply for the job or not

A basic XGBoost model with some manual hyperparameter tuning on Pima Indians Diabetes Database

This projet aims at building a Machine Learning model for predicting items outlet sales.

This project, done for GA Tech, explores relationship between health factors and hospitalization in NHANES dataset

House Price Prediction - Python, XGBoost, LightGBM

Lending Club Data Analysis

Python; Machine-Learning; XGBoost; LGBoost; Data Science; Kaggle Competition; Top 2% Marks Among All Competitors

Airbnb Price Predictor

A binary classifier for mortgage approvals, based on XGBoost.

Demonstrating how to build an XGBoost model and deploy it to Algorithmia, from a Jupyter notebook

restaurant-revenue-prediction project for the Kaggle competition: "Restaurant Revenue Prediction". While the competition is closed, my best submission would currently place me in the 98th percentile (top 2%) on the public leaderboard and the 99th percentile (top 1%) on the private leaderboard of the competition.

🔍Explore steel plate defect prediction with EDA, modelling, and multi-class classification 🛠

associate with Steel Plate Defect Prediction Playground Series - Season 4, Episode 3

Different ML Algorithms both in scripts & Jupyter Notebooks

In our team capstone project (Carlotta U., Silas M. and Jonas B.) of our bootcamp at neue fische churn prevention was applied to a dataset of the german newspaper “Die Zeit”. By predicting who is going to quit a subscription and doing churn prevention activities, a loss of subscribers can be avoided and revenues can be increased.

Multiclass & Multilabel Text Classification

In this project I used different text preprocessing techniques to preprocess my text data. The I used different classification algorithm to get the best results as it was a classification problem. I used Kaggles free GPUs and Datasets in this competion.