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A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

An open source python library for automated feature engineering

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

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

Feature engineering and selection open-source Python library compatible with sklearn.

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.

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

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

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.

Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.

Feature Engineering and Feature Importance in Machine Learning for Financial Markets

AI-powered NBA game outcome predictor that uses advanced team stats and trend-based features to forecast winners and track model performance

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.

A collection of pandas & scikit-learn compatible transformers for preprocessing and feature engineering 🛠