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.

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

Churn modelling for bank customers using Artificial Neural Network

NHL-Game Analysis 🥅 🏒

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.

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

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

Predicts calories burned during physical activity using publicly available workout and physiological data from Kaggle.

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

*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

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:

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

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 …

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

📈 Train yourself to make better predictions.

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.

Smoking Detection is a machine learning-based web application built with Flask that predicts the probability of a person being a smoker using various body signal inputs. This project leverages data science techniques and predictive modeling to provide health-related insights through an easy-to-use interface.

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.

Predictive Modelling – Exercises (in R)