There are 27 repositories under feature-extraction topic.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)
Automatic extraction of relevant features from time series:
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🔥🔥
特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现
OpenMLDB is an open-source machine learning database that provides a feature platform enabling consistent features for training and inference.
A low code Machine Learning service that personalizes articles, listings, search results, recommendations to boost user engagement. A friendly Learn-to-Rank engine
Feature engineering package with sklearn like functionality
:speech_balloon: SpeechPy - A Library for Speech Processing and Recognition: http://speechpy.readthedocs.io/en/latest/
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
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 framework that provides a simple API for developing ML-driven data processing and search pipelines.
Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
Features selector based on the self selected-algorithm, loss function and validation method
Highly comparative time-series analysis
An intuitive library to extract features from time series.
Machine Learning library for the web and Node.
A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
Fully Convolutional Geometric Features: Fast and accurate 3D features for registration and correspondence.
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.
PopSift is an implementation of the SIFT algorithm in CUDA.
:book: This guide is to help you understand the basics of the computerized image and develop computer vision projects with OpenCV. Includes Python, Java, JavaScript, C# and C++ examples.
:bar_chart: Computation and processing of models' parameters
A query language for performing computations on JSON-like structures. Tuned for clientside ML feature extraction.
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
Automated feature extraction in Python
.NET DSP library with a lot of audio processing functions
Use advanced feature engineering strategies and select best features from your data set with a single line of code.