A unified framework for machine learning with time series
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Updated
Jul 6, 2024 - Python
A unified framework for machine learning with time series
The machine learning toolkit for time series analysis in Python
A Python package for time series classification
Deep Learning for Time Series Classification
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
A toolkit for machine learning from time series
InceptionTime: Finding AlexNet for Time Series Classification
DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
Transfer learning for time series classification
Voice Activity Detection based on Deep Learning & TensorFlow
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
Data augmentation using synthetic data for time series classification with deep residual networks
PyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"
Deep Neural Network Ensembles for Time Series Classification
🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.
A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification
Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.
HYDRA: Competing convolutional kernels for fast and accurate time series classification
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