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

TA-Lib (Core C Library)

🌝 Lottery prediction besides of following "law of proability","Probability: Independent Events", there are still "Saying "a Tail is due", or "just one more go, my luck is due to change" is called The Gambler's Fallacy" existed.

Acycle: Time-series analysis software for research and education

I perform time series analysis of data from scratch. I also implement The Autoregressive (AR) Model, The Moving Average (MA) Model, The Autoregressive Moving Average (ARMA) Model, The Autoregressive Integrated Moving Average (ARIMA) Model, The ARCH Model, The GARCH model, Auto ARIMA, forecasting and exploring a business case.

Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data.

Experiments in climatological time series analysis using deep learning

Analysis of various climatological times series using Continuous Wavelets Transform

Cassandra NoSQL + Bokeh + Prophet for stock time series analysis

A React.js + Flask + MongoDB web application that details information on the Coronavirus, including datasets, news, a time series analysis, and vaccine distribution information. Utilizes 6 APIs in order to fetch and present data via a user friendly interface. Utilizes Chart.js & D3.js for mapping and dynamic visualizations.

A simple Time Series Analysis module for humans ⏰

1. Using facebook's Prophet to predict Bitcoin values. 2. Using Reddit comments and scores to measure time series sentiment, as a supplementary feature in a multivariate LSTM RNN.

This is an Analysis on Goldman Sachs Group Inc Stock Market Time Series featuring Prices starting from 2016 to present date, Written in R Language

Course materials and exercises for the Coursera: Practical Time Series Analysis from The State University of New York in Python.

Neste repositório será feita uma análise e modelagem de séries temporais das ações da magalu

Time series analysis on 2 datasets Adani and tata to analyse the past data within a given duration of time to forecast the future.

Assignments for Statistical Data Analysis course at UPM including performing statistical analysis, multiple linear regression, and time series analysis.

This repository provides code in R reproducing examples of the states space models presented in book "An Introduction to State Space Time Series Analysis" by J.J.F. Commandeur and S.J. Koopman.

Here we predict the Indian GDP StateWise using Simple MLP Neural Network and Time Series Analysis

Testing the hyphotesis of cointegration of two term structures through Dickey-Fuller tests and Engle-Granger causality. Finally I exploit the VECM to infer the model and through the Cholesky decomposition I analyze SIRF and FEVD