Anomaly detection for temporal data using LSTMs

List of papers, code and experiments using deep learning for time series forecasting

A Keras library for multi-step time-series forecasting.

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Machine Learning on Sequential Data Using a Recurrent Weighted Average

Statistical inference on machine learning or general non-parametric models

Feeding images of time series to Conv Nets! (Tensorflow + Keras)

Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971

Annotation of ECG signals using deep learning, tensorflow’ Keras

Library of autoencoders for sequential data

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

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.

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

Official code for UnICORNN (ICML 2021)

Machine learning models for time series analysis

A stock trading bot that uses machine learning to make price predictions.

GANs for time series generation in pytorch