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Various computer and robotic vision algorithms implemented from scratch.
Content aware image resize library
Automatic extraction of relevant features from time series:
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
Feature engineering package with sklearn like functionality
OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
A Python wrapper for Kaldi
An intuitive library to extract features from time series.
:speech_balloon: SpeechPy - A Library for Speech Processing and Recognition: http://speechpy.readthedocs.io/en/latest/
Highly comparative time-series analysis
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.