1225 Open source projects that are alternatives of or similar to Time-Series-Forecasting

Resources for working with time series and sequence data

Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.

Highly comparative time-series analysis

A COVID-19 dataset with 90 World countries including Algeria.

COVID-19 spread shiny dashboard with a forecasting model, countries' trajectories graphs, and cluster analysis tools

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

Axibase Time Series Database: Usage Examples and Research Articles

AtsPy: Automated Time Series Models in Python (by @firmai)

TSrepr: R package for time series representations

A machine learning toolkit dedicated to time-series data

Technical Analysis Library Time-Series

Anomaly detection for temporal data using LSTMs

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

Predict time-series with one line of code.

Stock Price Prediction using Machine Learning Techniques

Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs

A python multi-variate time series prediction library working with sklearn

A unified framework for machine learning with time series

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

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

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

GANs for time series generation in pytorch

Anything can happen in the next half hour (including spectral timing made easy)!

An open source library for Fuzzy Time Series in Python

Library of autoencoders for sequential data

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

🚂 Python API for Emma's Markov Model Algorithms 🚂

An End-to-end Outlier Detection System

R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

Using LSTM network for time series forecasting

Code examples for pyFTS

Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)

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

Singular Spectrum Analysis for time series forecasting in Python

A framework for historical volatility estimation and analysis.

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

Analyzes chronological patterns present in time-series data and provides human-readable descriptions

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

List of awesome papers about time series, mainly including algorithms based on machine learning | 收录时间序列分析中各个研究领域的高水平文章，主要包含基于机器学习的算法

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

Fast & scalable MCMC for all your exoplanet needs!

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.

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.

A framework for systemic risk valuation and analysis.

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.

Annotation of ECG signals using deep learning, tensorflow’ Keras

A use-case focused tutorial for time series forecasting with python

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

Stock Analysis Tutorial in Python

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.

The Most Advanced Time Series Platform

Time series market data

Scalpel: The Python Static Analysis Framework

A static binary vulnerability scanner

Functions for easily making publication-quality figures with matplotlib.

Hands-on in-person workshop for Deep Learning with TensorFlow

GreyCat - Data Analytics, Temporal data, What-if, Live machine learning

Detailed analysis of your Energy, gas and liquid consumptions

Implementation of Conway's Surreal Numbers