feature-engineering
There are 3316 repositories under feature-engineering topic.
microsoft/nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
EpistasisLab/tpot
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
alteryx/featuretools
An open source python library for automated feature engineering
alibaba/Alink
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
mljar/mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
apachecn/fe4ml-zh
:book: [译] 面向机器学习的特征工程
Visualize-ML/Book6_First-Course-in-Data-Science
Book_6_《数据有道》 | 鸢尾花书：从加减乘除到机器学习；欢迎大家批评指正！纠错多的同学会得到赠书感谢！
salesforce/TransmogrifAI
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning
metarank/metarank
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
DAGWorks-Inc/hamilton
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
feature-engine/feature_engine
Feature engineering package with sklearn like functionality
rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
feathr-ai/feathr
Feathr – A scalable, unified data and AI engineering platform for enterprise
featureform/featureform
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
ClimbsRocks/auto_ml
[UNMAINTAINED] Automated machine learning for analytics & production
4paradigm/OpenMLDB
OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
Yimeng-Zhang/feature-engineering-and-feature-selection
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
LastAncientOne/Deep_Learning_Machine_Learning_Stock
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
asavinov/intelligent-trading-bot
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
winedarksea/AutoTS
Automated Time Series Forecasting
logicalclocks/hopsworks
Hopsworks - Data-Intensive AI platform with a Feature Store
DeepWisdom/AutoDL
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
functime-org/functime
Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
NVIDIA-Merlin/NVTabular
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.
fraunhoferportugal/tsfel
An intuitive library to extract features from time series.
sberbank-ai-lab/LightAutoML
LAMA - automatic model creation framework
stitchfix/hamilton
A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
alteryx/evalml
EvalML is an AutoML library written in python.
abhayspawar/featexp
Feature exploration for supervised learning
jeongyoonlee/Kaggler
Code for Kaggle Data Science Competitions
HouJP/kaggle-quora-question-pairs
Kaggle：Quora Question Pairs, 4th/3396 (https://www.kaggle.com/c/quora-question-pairs)
HunterMcGushion/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
ashishpatel26/Amazing-Feature-Engineering
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
google/temporian
Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖
duxuhao/Feature-Selection
Features selector based on the self selected-algorithm, loss function and validation method
AutoViML/featurewiz
Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.