skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

This repository contains the data analytics lessons I took from the bootcamp between 5 Jan - 4 Aug 2022 and includes 48 sessions, 10 labs, 12 assignments, 12 weekly agendas, and 5 projects.

Churn modelling for bank customers using Artificial Neural Network

Regression models for "epigenetic clock" estimation of canine chronological age

A data-driven approach to assess property prices in a Midwestern state, using regression and decision tree models to evaluate housing data from 2006-2010.

NHL-Game Analysis 🥅 🏒

Show case for modelStudio based on ⚽⚽⚽FIFA 20 ⚽⚽⚽

Given the dataset, can we predict the Co2 emission of a car using another field such as engine size?

Predictive Modelling of Pathological Complete Response Classification and Relapse-Free Survival Regression in Cancer Patients

This repo contains the code (data analysis, models, results) of my diploma thesis with title "A recommender system to predict the behaviour of an e-commerce page visitor". The official university's listing of this thesis is on the link bellow:

Customer Churn is a burning problem for Telecom companies. In this project, we simulate one such case of customer churn where we work on a data of postpaid customers with a contract. The data has information about the customer usage behavior, contract details and the payment details. The data also indicates which were the customers who canceled …

Perform exploratory data analysis techniques, such as predictive models and advanced visualization, on the Boston Housing Dataset.

Analyze the impact of COVID-19 on Airbnb bookings in Chicago and Boston, focusing on changes in traveler preferences, occupancy rates, and revenue

This is a group project in the Data Science for Business I course where we took a data-driven approach to foster employee retention and enhance operational efficiency by building predictive models on Python.

📈 Train yourself to make better predictions.

Develop classification strategies and preprocess data with pandas to prepare for predicative modeling.

topsis package created which can be directly used through command line or terminal for ranking of information provided

Profiles of healthy people and diabetic people were analyzed and used to build a predictive model to gauge the diabetes risk index of an untested person.

*Credit Risk Analysis App** is a machine learning-powered web application designed to help financial institutions and lenders assess borrower default risk in real-time. Built with Python and Streamlit

Predictive Modelling – Exercises (in R)