skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
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Updated
Sep 18, 2024 - Python
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 clarusway 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
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 ⚽⚽⚽
NHL-Game Analysis 🥅 🏒
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:
Perform exploratory data analysis techniques, such as predictive models and advanced visualization, on the Boston Housing Dataset.
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.
topsis package created which can be directly used through command line or terminal for ranking of information provided
📈 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.
Predictive Modelling – Exercises (in R)
Here I provide a sample of one of my consultations. I was reached out to consult on how to approach a predictive model for customer churn for an investment banking company.
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 …
Develop classification strategies and preprocess data with pandas to prepare for predicative modeling.
Analyze the impact of COVID-19 on Airbnb bookings in Chicago and Boston, focusing on changes in traveler preferences, occupancy rates, and revenue
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