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Search results for machine learning feature engineering
feature-engineering
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machine-learning
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167 search results found
Nni
⭐
13,725
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Tpot
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9,516
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Featuretools
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7,035
An open source python library for automated feature engineering
Alink
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3,479
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
Mljar Supervised
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2,867
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Fe4ml Zh
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2,467
📖 [译] 面向机器学习的特征工程
Transmogrifai
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2,099
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
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1,949
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
Feathr
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1,886
Feathr – A scalable, unified data and AI engineering platform for enterprise
Featureform
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1,716
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
Feature_engine
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1,651
Feature engineering package with sklearn like functionality
Openmldb
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1,511
OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
Auto_ml
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1,442
[UNMAINTAINED] Automated machine learning for analytics & production
Hamilton
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1,388
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
Sgx Full Orderbook Tick Data Trading Strategy
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1,151
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Deep_learning_machine_learning_stock
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1,093
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
Hopsworks
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1,041
Hopsworks - Data-Intensive AI platform with a Feature Store
Nvtabular
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1,010
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.
Autodl
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999
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
Autots
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935
Automated Time Series Forecasting
Hamilton
⭐
877
A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
Feature Engineering And Feature Selection
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798
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Lightautoml
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769
LAMA - automatic model creation framework
Functime
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768
Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
Kaggler
⭐
723
Code for Kaggle Data Science Competitions
Evalml
⭐
679
EvalML is an AutoML library written in python.
Featexp
⭐
656
Feature exploration for supervised learning
Intelligent Trading Bot
⭐
650
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
Hyperparameter_hunter
⭐
635
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Handson Unsupervised Learning
⭐
604
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
Complete Life Cycle Of A Data Science Project
⭐
499
Complete-Life-Cycle-of-a-Data-Science-Project
Amazing Feature Engineering
⭐
485
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.
Open_source_demos
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478
A collection of demos showcasing automated feature engineering and machine learning in diverse use cases
Hyperactive
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475
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
Feature Selection
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475
Features selector based on the self selected-algorithm, loss function and validation method
Open Solution Home Credit
⭐
444
Open solution to the Home Credit Default Risk challenge 🏡
Automl Implementation For Static And Dynamic Data Analytics
⭐
443
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
Gan For Tabular Data
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442
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.
Deltapy
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411
DeltaPy - Tabular Data Augmentation (by @firmai)
Autofeat
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410
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Mistql
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331
A query / expression language for performing computations on JSON-like structures. Tuned for clientside ML feature extraction.
Awesome Feature Engineering
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316
A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
Feature Engineering For Machine Learning
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314
Code repository for the online course Feature Engineering for Machine Learning
Serverless Ml Course
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296
Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features
Nyaggle
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276
Code for Kaggle and Offline Competitions
Upgini
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272
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
My Data Competition Experience
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271
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
Feathub
⭐
255
FeatHub - A stream-batch unified feature store for real-time machine learning
Feature Engineering Tutorials
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217
Data Science Feature Engineering and Selection Tutorials
Geomancer
⭐
194
Automated feature engineering for geospatial data
The Data Science Workshop
⭐
156
A New, Interactive Approach to Learning Data Science
Albedo
⭐
142
A recommender system for discovering GitHub repos, built with Apache Spark
Datasist
⭐
137
A Python library for easy data analysis, visualization, exploration and modeling
Raptor
⭐
136
Transform your pythonic research to an artifact that engineers can deploy easily.
Feature Engineering Handbook
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127
A practical feature engineering handbook
Tpot2
⭐
118
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Evolutionaryforest
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108
An open source python library for automated feature engineering based on Genetic Programming
Bdc2019
⭐
98
2019中国高校计算机大赛——大数据挑战赛 第三名解决方案
Go Featureprocessing
⭐
98
🔥 Fast, simple sklearn-like feature processing for Go
Nba_betting
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93
Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.
Nitrofe
⭐
84
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
Arfs
⭐
80
All Relevant Feature Selection
Anovos
⭐
78
Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
Autogbt Alt
⭐
73
An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.
Home Credit Default Risk
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59
Default risk prediction for Home Credit competition - Fast, scalable and maintainable SQL-based feature engineering pipeline
Caafe
⭐
55
Semi-automatic feature engineering process using Language Models and your dataset descriptions. Based on the paper "LLMs for Semi-Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering" by Hollmann, Müller, and Hutter (2023).
Mindware
⭐
54
An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Fxy
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53
Security-Scenes-Feature-Engineering-Toolkit, Continuous Integration.一款安全数据特征化工具
Mlnotebooks
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52
Demonstration notebooks for Machine Learning
Protr
⭐
50
🧬 Toolkit for generating various numerical features of protein sequences
Featuretoolsr
⭐
49
An R interface to the Python module Featuretools
Autotabular
⭐
45
Automatic machine learning for tabular data. ⚡🔥⚡
Build And Deploy Real Time Feature Pipeline
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45
Develop and deploy a real-time feature pipeline in Python, using Bytewax 🐝 and Hopsworks Feature Store.
Awesome Feature Engineering
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43
A curated list of feature engineering techniques for image and text machine learning
Data Science Regular Bootcamp
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39
Regular practice on Data Science, Machien Learning, Deep Learning, Solving ML Project problem, Analytical Issue. Regular boost up my knowledge. The goal is to help learner with learning resource on Data Science filed.
Datacook
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38
Machine Learning and Data Analysis in JavaScript.
Bytewax Hopsworks Example
⭐
37
Compute and store real-time features for crypto trading using Bytwax (stream processing) and Hopsworks (Feature Store)
Ml Forecast Features Eng
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37
Machine Learning for Retail Sales Forecasting — Features Engineering
Ds2
⭐
37
Easiest way to use AI models without coding (Web UI & API support)
Cooka
⭐
36
A lightweight and visual AutoML system
Kaggle Berlin
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36
Material of the Kaggle Berlin meetup group!
Feagen
⭐
33
(deprecated) A fast and memory-efficient Python data engineering framework for machine learning.
Edaspy
⭐
30
Estimation of Distribution algorithms Python package
Rsafe
⭐
28
Surrogate Assisted Feature Extraction in R
Drugs Recommendation Using Reviews
⭐
27
Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.
Feng
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27
feng - feature engineering for machine-learning champions
Guided Machine Learning
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26
Self learning guide for machine learning
Predicting Transportation Modes Of Gps Trajectories
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24
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 generation; (iii) trajectory features extraction; (iv) noise removal; (v) normalization. We show that the extraction of the new point features: bearing rate
Spotify_song_recommender
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24
This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.
Clinical_nlp_elastic
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23
Clinical NLP Analysis with Elasticsearch and Kibana
Disentangled Attribution Curves
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23
Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
Data Science End To End
⭐
22
A Respository to get you job ready as a Data Scientist
Bytehub
⭐
22
ByteHub: making feature stores simple
Geometricus
⭐
22
A structure-based, alignment-free embedding approach for proteins. Can be used as input to machine learning algorithms.
Zca
⭐
21
ZCA whitening in python
Fifa 2019 Analysis
⭐
21
This is a project based on the FIFA World Cup 2019 and Analyzes the Performance and Efficiency of Teams, Players, Countries and other related things using Data Analysis and Data Visualizations
Kivyandroidclassification
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21
Image Classification for Android using Artificial Neural Network using NumPy and Kivy.
Sklearn Audio Classification
⭐
19
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
Skrobot
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19
skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
Predict Household Poverty
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18
Predict the poverty of households in Costa Rica using automated feature engineering.
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