Projeto de ensino para o curso Ciência de Dados ministrado por mim na Hashtag
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Updated
Jul 17, 2024 - Jupyter Notebook
Projeto de ensino para o curso Ciência de Dados ministrado por mim na Hashtag
An collection of machine learning projects implemented based on IEEE papers.
Simple End-to-End Machine Learning Project
Predicting the Residential Energy Usage across 113.6 million U.S. households using Machine Learning Algorithms (Regression and Ensemble)
This repository includes projects using datasets of structured data (non-Spark). The projects use Python, NumPy, Pandas, Matplotlib, Seaborn, TensorFlow, Pytorch, and Sklearn.
Visual tool to explore variants of Polis-like data pipelines.
Simple Application for predicting price of the flight. It uses sklearn pipeline to perform preprocessing , feature selection and feature engineering and model building .The pipeline object is saved in a pickle file and used in the flask application for prediction
Here are some fun projects to learn ML using Handson approach
A simple classifier trained on a small tabular dataset using scikit-learn to demonstrate how pipelines are used and how they work.
End-to-end supervised machine learning regression pipeline with data cleaning, imputation, leakage-aware splitting (time-based validation), and multi-model benchmarking to predict a key operational drilling target.
Regression Problem
ChurnIQ is a Streamlit app that predicts customer churn based on inputted customer details. Using a trained machine learning model, it helps businesses anticipate whether customers will stay or leave
this repo will include all my work regarding NLP
Predicting developer's salary from Stack Overflow Annual Developer Survey (https://insights.stackoverflow.com/survey)
End-to-end machine learning pipeline to classify disaster messages into 36 categories and a web app to deploy the trained model.
Binary income classification on the UCI Adult Census dataset. Compares Logistic Regression, Gradient Boosting, and Random Forest through a complete sklearn pipeline — 85.65% accuracy, ROC-AUC 0.91.
[COMMUNITY] — Spatial Join & Enrich any urban layer given any external urban dataset of interest, streamline your urban analysis with Scikit-Learn-Like pipelines, and share your insights with the urban research community!
⚡ Code for machine Learning Pipeline with Scikit-learn ⚡
Logistic regression pipeline by using sklearn, feature_engine, joblib
Machine learning (ML) pipelines consist of several steps to train a model.
To associate your repository with the sklearn-pipeline topic, visit your repo's landing page and select "manage topics."