Repositório para armazenar códigos do projeto.

This repository showcases a Python project using Machine learning Algorithms/ Models on Churn Analysis in the telecommunication industry. By leveraging Machine Learning techniques, I strive to help telecom providers reduce churn rates, improve customer retention, and make data-driven decisions.

AutoML web app using streamlit and pycaret

This is a sample application that demonstrates how to build a regression AutoML app using Streamlit, Pandas Profiling, and PyCaret.

This is a sample application that demonstrates how to build a classification AutoML app using Streamlit, Pandas Profiling, and PyCaret.

This is a Web application built using streamlit whcih inputs the user dataset and auto Profiles and makes classification model using Pycreat.

Basic EDA, Model

GoodData and Machine Learning

A streamlit webapp for automated eda to help you explore your dataset.

Testing PyCaret, Fugue, and Dask

An automated machine learning pipeline for EAF process data using Streamlit library.

Anomaly Detection using Isolated Forests, K Nearest Neighbours using PyCaret Library. Dataset consists of mostly categorical data, used Cardinal Encoding instead of OHE

An app that utilizes streamlit and pycaret to automate a machine learning pipeline

Machine Learning Web application for process and machine learning model for classifying organisms at a taxonomical level

The Automated ML web app project leverages Python along with Pandas Profiling, PyCaret, and Streamlit to provide a seamless and user-friendly experience for automating machine learning workflows. It enables users to effortlessly explore, preprocess, model, and download the trained model

AutoML Web Frontend for automated Data Science

Create your own Spotify recommendation tool

Give Everybody ML