1816 Open source projects that are alternatives of or similar to Flow Forecast

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.

LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION

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

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

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Modeltime unlocks time series forecast models and machine learning in one framework

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Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

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

This library provides a set of basic functions for different type of deep learning (and other) algorithms in C.This deep learning library will be constantly updated

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

GPU-Accelerated Deep Learning for Time Series using Modeltime GluonTS (Learning Lab 53). Event sponsors: Saturn Cloud, NVIDIA, & Business Science.

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

Open-source benchmark datasets and pretrained transformer models in the Filipino language.

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Library of autoencoders for sequential data

Time series analysis in Java

Anomaly detection for temporal data using LSTMs

An open source library for Fuzzy Time Series in Python

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

Gaussian dynamic Bayesian networks structure learning and inference based on the bnlearn package

A toolkit for working with time series in R

Probabilistic time series modeling in Python

Rainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.

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.

Python package for early warning signals (EWS) of bifurcations in time series data.

sknifedatar is a package that serves primarily as an extension to the modeltime 📦 ecosystem. In addition to some functionalities of spatial data and visualization.

Using LSTM network for time series forecasting

Scalable machine 🤖 learning for time series forecasting.

Context-Transformer: Tackling Object Confusion for Few-Shot Detection, AAAI 2020

Time Series Forecasting Best Practices & Examples

LSTM to predict wind speed

MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems

CentOS based Docker container for Time Series Analysis and Modeling.

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

📈 high level wrapper for parallel univariate time series forecasting 📉

📈 PyTorch dual-attention LSTM-autoencoder for multivariate Time Series 📈

This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

Forecasting Solar Power: Analysis of using a LSTM Neural Network

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Merlion: A Machine Learning Framework for Time Series Intelligence

resources for the IBM Airlines Table-Question-Answering Benchmark

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Transfer learning for time series classification

PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.

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Voice Activity Detection based on Deep Learning & TensorFlow

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