Automatic extraction of relevant features from time series:
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Updated
Aug 3, 2024 - 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.
特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现
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.
Audio feature extraction for JavaScript.
A cross-platform video structuring (video analysis) framework. If you find it helpful, please give it a star: ) 跨平台的视频结构化(视频分析)框架,觉得有帮助的请给个星星 : )
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
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
A Python wrapper for Kaldi
An intuitive library to extract features from time series.
Face Recognition on NIST FRVT Top Ranked ,Face Liveness Detection Engine on iBeta 2 Certified, 3D Face Anti Spoofing, Face Detection, Face Matching, Face Analysis, Face Sentiment, Face Alignment, Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution on Android
💬 SpeechPy - A Library for Speech Processing and Recognition: http://speechpy.readthedocs.io/en/latest/
Highly comparative time-series analysis
Features selector based on the self selected-algorithm, loss function and validation method
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