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activity_segmentation

Embedding-based real-time change point detection with application to activity segmentation in smart home time series data

awesome-algorithm

Leetcode 题解 (跟随思路一步一步撸出代码) 及经典算法实现

bayesian_changepoint_detection

Methods to get the probability of a changepoint in a time series.

cs231nassignment

Stanford CS231n assignment in 2019 spring

dain

Deep Adaptive Input Normalization for Time Series Forecasting

deep_crs_him8

A deep learning approach to CRS model from Himawari8 data

deepconvlstm

Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers

google-research

Google Research

hoof-based-medetection

A python program to detect micro expression(ME) in video with HOOF descriptors and SVM classifier

keras-seq-2-seq-signal-prediction

An implementation of a sequence to sequence neural network using an encoder-decoder

medetection

nab

The Numenta Anomaly Benchmark

onlinerpca

Online Robust Principal Component Analysis

paho.mqtt.python

paho.mqtt.python

seq2seq-signal-prediction

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

telemanom

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

time-series-autoencoder

:chart_with_upwards_trend: PyTorch dual-attention LSTM-autoencoder for multivariate Time Series :chart_with_upwards_trend:

video-classification-cnn-and-lstm-

To classify video into various classes using keras library with tensorflow as back-end.