Automatic extraction of relevant features from time series:
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Updated
Nov 15, 2025 - Jupyter Notebook
Automatic extraction of relevant features from time series:
A PyTorch implementation of EfficientNet
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
High-Performance Face Recognition Library on PaddlePaddle & PyTorch
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
A cross-platform video structuring (video analysis) framework. If you find it helpful, please give it a star: ) Kua Ping Tai De Shi Pin Jie Gou Hua (Shi Pin Fen Xi )Kuang Jia ,Jue De You Bang Zhu De Qing Gei Ge Xing Xing : )
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
Te Zheng Ti Qu /Shu Ju Jiang Wei :PCA, LDA, MDS, LLE, TSNEDeng Jiang Wei Suan Fa De pythonShi Xian
Feature engineering and selection open-source Python library compatible with sklearn.
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Audio feature extraction for JavaScript.
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics
An intuitive library to extract features from time series.
A Python wrapper for Kaldi
SpeechPy - A Library for Speech Processing and Recognition: http://speechpy.readthedocs.io/en/latest/
Highly comparative time-series analysis
The Munich Open-Source Large-Scale Multimedia Feature Extractor
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.
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