Feature Store for Machine Learning
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Updated
May 27, 2023 - Python
Feature Store for Machine Learning
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
Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness" (ICLR 2019 Oral)
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.
FeatureHub - cloud native feature flags, A/B testing and remote configuration service. Real-time streaming feature updates. Provided with Java, JavaScript, React, Python, Go, .Net, Ruby, Android, Swift and Flutter SDKs.
Data Science Feature Engineering and Selection Tutorials
Bonnet and then some! Deep Learning Framework for various Image Recognition Tasks. Photogrammetry and Robotics Lab, University of Bonn
Why you should bump your Android app minsdk?
Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML pipeline from hundreds of public and premium external data sources optimized for ML models with LLMs and other NNs
Calculates various features from time series data. Python implementation of the R package tsfeatures.
Features and tweaks to R that I and others would love to see - feel free to add yours!
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
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