PhoBERT-Extraction

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.

Features selector based on the self selected-algorithm, loss function and validation method