NyaggleCode for Kaggle and Offline Competitions
Stars: ✭ 209 (+620.69%)
Mutual labels: feature-engineering
msdaLibrary 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
Stars: ✭ 80 (+175.86%)
Mutual labels: feature-engineering
fengfeng - feature engineering for machine-learning champions
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Mutual labels: feature-engineering
AutoTSAutomated Time Series Forecasting
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Mutual labels: feature-engineering
LightautomlLAMA - automatic model creation framework
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Mutual labels: feature-engineering
PubMed-Best-MatchMachine-learning based pipeline relying on LambdaMART currently used in PubMed for relevance (Best Match) searches
Stars: ✭ 36 (+24.14%)
Mutual labels: feature-engineering
clinkClink 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.
Stars: ✭ 24 (-17.24%)
Mutual labels: feature-engineering
featuretoolsOnSparkA simplified version of featuretools for Spark
Stars: ✭ 24 (-17.24%)
Mutual labels: feature-engineering
tsflexFlexible time series feature extraction & processing
Stars: ✭ 252 (+768.97%)
Mutual labels: feature-engineering
FIFA-2019-AnalysisThis 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
Stars: ✭ 28 (-3.45%)
Mutual labels: feature-engineering
skrobotskrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
Stars: ✭ 22 (-24.14%)
Mutual labels: feature-engineering
Amazing Feature EngineeringFeature 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.
Stars: ✭ 218 (+651.72%)
Mutual labels: feature-engineering
exemplary-ml-pipelineExemplary, annotated machine learning pipeline for any tabular data problem.
Stars: ✭ 23 (-20.69%)
Mutual labels: feature-engineering
TsfelAn intuitive library to extract features from time series
Stars: ✭ 202 (+596.55%)
Mutual labels: feature-engineering
kaggle-berlinMaterial of the Kaggle Berlin meetup group!
Stars: ✭ 36 (+24.14%)
Mutual labels: feature-engineering
anovosAnovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
Stars: ✭ 77 (+165.52%)
Mutual labels: feature-engineering
EvolutionaryForestAn open source python library for automated feature engineering based on Genetic Programming
Stars: ✭ 56 (+93.1%)
Mutual labels: feature-engineering