Mfd Alternatives

Multispectral Feature Descriptor (MFD).
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Alternatives To cfgnunes/mfd
Project Name Stars Downloads Repos Using This Packages Using This Most Recent Commit Total Releases Latest Release Open Issues License Language
blue-yonder/tsfresh 7,824 33 44 over 2 years ago 30 June 14, 2023 63 mit Jupyter Notebook
Automatic extraction of relevant features from time series:
lukemelas/EfficientNet-PyTorch 6,577 7 36 over 4 years ago 13 April 15, 2021 133 apache-2.0 Python
A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)
BoltzmannEntropy/interviews.ai 3,146 0 0 about 4 years ago 0 4
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.
ZhaoJ9014/face.evoLVe 3,074 0 0 over 3 years ago 0 84 mit Python
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
towhee-io/towhee 2,903 0 0 about 2 years ago 26 December 04, 2023 3 apache-2.0 Python
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
CyberZHG/keras-bert 2,281 20 13 about 4 years ago 98 January 22, 2022 0 mit Python
Implementation of BERT that could load official pre-trained models for feature extraction and prediction
heucoder/dimensionality_reduction_alo_codes 1,949 0 0 almost 3 years ago 0 4 apache-2.0 Python
特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现
metarank/metarank 1,949 0 0 about 2 years ago 0 95 apache-2.0 Scala
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
MaxBenChrist/awesome_time_series_in_python 1,811 0 0 about 3 years ago 0 4
This curated list contains python packages for time series analysis
LastAncientOne/Deep_Learning_Machine_Learning_Stock 1,721 0 0 about 2 years ago 0 4 mit Jupyter Notebook
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
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