data-cleaning-pipeline

🤖 An automated machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers). Python 3.6 required.

Learn2Clean: Optimizing the Sequence of Tasks for Data Preparation and Cleaning

A Python library for Automated Exploratory Data Analysis, Automated Data Cleaning, and Automated Data Preprocessing For Machine Learning and Natural Language Processing Applications in Python.

中文对话数据清洗

CleanEasy is a powerful, user-friendly Python library designed to simplify data cleaning and preprocessing for data scientists and analysts

Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health practitioners.

Machine Learning in Data Preprocessing & Deduplication

A Python library for day to day data analysis and machine learning. This aims to make data building, cleaning and machine learning much much faster. A library of extension and helper modules for Python's data analysis and machine learning libraries.

Create a machine learning pipeline, that categorizes disaster events.

excel, markdown, csv, sql 数据源批量/单独格式互相转换

Automating the data preprocessing pipeline

Data cleaning pipeline applied to retail sales dataset with anomalies

A full-stack data analytics pipeline using DBT, FastAPI, Streamlit and Postgres. Transforms raw data into modeled tables and exposes KPIs via API endpoints, with an interactive dashboard for visualization.

Data Preprocessing Pipeline — A modular Python pipeline that transforms messy, raw data into clean, structured, analysis-ready datasets. Reads CSV/Excel files, then normalizes column names, strips whitespace, removes duplicates, and intelligently resolves missing values by data type. Validates the result against required schemas and quality rules.

This is replicable exploratory data analysis of Peru SINADEF database (death index) of covid-19 related cases.

Language model assisted data cleaning

Data ETL for machine learning with dockerizing, including data crawling, data transforming/cleaning, and saving data to s3

This data analysis and visualization project aimed at presenting the work of OBA-Floripa NGO to authorities and the general population. The idea is to claim the need for continued funding resources, given the positive impact of the organization's activities on public health issues.

MAHA is an in-progress ETL package which uses machine learning to clean your dataset with one line command.

The dataset I wrangled (and analysed and visualized) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog.