dustin-decker/featuremill
general-purpose fast, stateless, and deterministic feature extractor written in golang for use in machine learning
This tool helps machine learning engineers quickly convert raw data like text, timestamps, IP addresses, and numerical values into a standardized format ready for machine learning algorithms. It takes your raw data inputs and efficiently outputs them as a series of numerical features in the libsvm format. It's designed for machine learning practitioners building high-throughput systems.
No commits in the last 6 months.
Use this if you need to rapidly and consistently transform various types of raw data into machine learning features for online prediction or large-scale batch processing.
Not ideal if your machine learning model heavily relies on complex text transformations like Inverse Document Frequency (IDF) or requires extensive stateful feature engineering.
Stars
12
Forks
—
Language
Go
License
Apache-2.0
Category
Last pushed
Mar 17, 2018
Commits (30d)
0
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