92 Open source projects that are alternatives of or similar to Awesome Feature Engineering

🔥 Fast, simple sklearn-like feature processing for Go

Automatic machine learning for tabular data. ⚡🔥⚡

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

🏆DataCon大数据安全分析大赛，2019年方向二（恶意代码检测）冠军源码、2020年方向五（恶意代码分析）季军源码

An open source python library for automated feature engineering based on Genetic Programming

This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Code for Kaggle Data Science Competitions

Solutions and figures for problems from Reinforcement Learning: An Introduction Sutton&Barto

Automatic feature engineering using Generative Adversarial Networks using TensorFlow.

Fast k-Nearest Neighbors Classifier for Large Datasets

Clink is a library that provides APIs and infrastructure to facilitate the development of parallelizable feature engineering operators that can be used in both C++ and Java runtime.

DeltaPy - Tabular Data Augmentation (by @firmai)

Package for Heart Rate Variability analysis in Python

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Implementation of feature engineering from Feature engineering strategies for credit card fraud

Feature engineering package with sklearn like functionality

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL [email protected]

Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark

使用sklearn做特征工程

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

Automated Time Series Forecasting

Icicle Streaming Query Language

An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP

feng - feature engineering for machine-learning champions

A collection of demos showcasing automated feature engineering and machine learning in diverse use cases

A schema-aware Scala library for data transformation

Feature exploration for supervised learning

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features gen…

Comprehensive toolkit for generating various numerical features of protein sequences

Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand

No description or website provided.

A scalable general purpose micro-framework for defining dataflows. You can use it to create dataframes, numpy matrices, python objects, ML models, etc.

An open source python library for automated feature engineering

Paraphrase question identification using Feature Fusion Network (FFN).

Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby

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.

(deprecated) A fast and memory-efficient Python data engineering framework for machine learning.

ZCA whitening in python

This repository contains instructions and code to deploy a customer 360 profile solution on Azure stack using the Cortana Intelligence Suite.

Machine-learning based pipeline relying on LambdaMART currently used in PubMed for relevance (Best Match) searches

Features selector based on the self selected-algorithm, loss function and validation method

Exemplary, annotated machine learning pipeline for any tabular data problem.

A miniature lisp-like language for querying JSON-like structures. Tuned for clientside ML feature extraction.

A simplified version of featuretools for Spark

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

Use advanced feature engineering strategies and select best features from your data set with a single line of code.

Material of the Kaggle Berlin meetup group!

A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning

Engine X - 实时AI智能决策引擎、规则引擎、风控引擎、数据流引擎。 通过可视化界面进行规则配置，无需繁琐开发，节约人力，提升效率，实时监控，减少错误率，随时调整； 支持规则集、评分卡、决策树，名单库管理、机器学习模型、三方数据接入、定制化开发等；

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

Kaggle：Quora Question Pairs, 4th/3396 (https://www.kaggle.com/c/quora-question-pairs)

Open solution to the Home Credit Default Risk challenge 🏡

Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales