🔬motif-learn: machine learning in scanning transmission electron microscopy

Featransform: Automated Feature Engineering for Supervised Machine Learning

Comprehensive notes and code on Python, data analysis, visualization, machine learning, and deep learning from my data science learning journey.

This repository hosts Python code that utilizes the Scikit-learn preprocessing API for data preprocessing. The code presents a comprehensive range of tools that handle missing data, scale data, encode categorical variables, and perform other functions.

Self analytics project on daily-frequency ridership data for various public transport services across the country. Sourced from data.gov.my(Prasarana/MyRapid)

A database-like benchmark of feature generation from time-series data

Conducted research in the fusion of machine learning models to improve stock market index prediction accuracy. Evaluated individual models (LSTM, RF, LR, GRU) and compared their performance to fusion prediction models (RF-LSTM, RF-LR, RFGRU).

Up to 90% accuracy with just 5 features using KNN algorithm and PCA for feature engineering. The dataset contained less than 1000 observations. The model's accuracy could be improved using more observations, further hyperparameter optimization and feature engineering

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

Feature engineering package with sklearn like functionality

Assignments of Data-Science(COSE471 김진규)

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Cloud-based AI / ML workflow and data application development framework

Docs for Chalk AI

An open source python library for automated feature engineering

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

CANtropy: Time Series Feature Extraction-Based Intrusion Detection Systems for Controller Area Networks

A Gradio machine learning application that predicts Danish car prices. Project includes web scraping, feature engineering, model creation and deployment