forcasting
There are 1 repository under forcasting topic.
hushuguo / awesome-time-series-papers
This repository offers a collection of recent time series research papers, including forecasting, anomaly detection and so on , with links to code and resources.
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rakesh-yadav / PyTorch-RNN-Tutorial
PyTorch tutorial for using RNN and Encoder-Decoder RNN for time series forecasting
Language:Jupyter Notebook 34- AI4VN2022-Air-Quality-Forecasting-Challenge
nqbinhcs / AI4VN2022-Air-Quality-Forecasting-Challenge
Runner-up team (2nd place) in AI4VN2022: Air Quality Forcasting Challenge
Language:Python 32 superkailang / WPP2012
A combined LSTM and LightGBM framework for improving deterministic and probabilistic wind energy forecasting
Language:Python 29fares-ds / Predicting-the-closing-stock-price-of-APPLE-using-LSTM
In this project we will be looking at data from the stock market, particularly some technology stocks. We will learn how to use pandas to get stock information, visualize different aspects of it, and finally we will look at a few ways of analyzing the risk of a stock, based on its previous performance history.
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t0mer / py-weatheril
weatheril is an unofficial [IMS](https://ims.gov.il) (Israel Meteorological Service) python API wrapper.
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timlynar / Containerized-Forecasting-Workflow
Scripts to build and run WRF and WPS in docker
Language:Python 9C-DragonAI / StockLLM
StockLLM: A Stock Analyzer with Comprehensive LLM Insights
Language:Python 8AsifMahsud / pakOrbit
Weather forcast application using 7times api
Language:JavaScript 7jgroth1 / Project_1_Coffee_Price_Predictors
Description of The coffee market and Arabica commodity price forecasting
Language:Jupyter Notebook 7Polaris000 / EarthquakeForecasting
A simple approach to earthquake forecasting
Language:Jupyter Notebook 6Jash-1 / Bitcoin-Prediction
Bitcoin-Stock-price-prediction-with-Time-series-FBprophet- Time Series Analysis in Python
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dipcode-software / wordpress-plugin-ipma-weather-widget
WordPress plugin providing a widget to display real-time forecast for any location in Portugal (mainland and archipelagos) in a WordPress website
Language:PHP 4SeyedMuhammadHosseinMousavi / Forecasting-SARS-CoV-2-Next-Wave-in-Iran-and-the-World-Using-TSK-Fuzzy-Neural-Networks
Forecasting SARS-CoV-2 Next Wave in Iran and the World Using TSK Fuzzy Neural Networks
Language:MATLAB 4Yairz1 / AutoEncoder
An implementation of AE LSTM based. We test our architecture on several tasks as reconstructing synthetic time series, s&p 500 stocks, and forecasting s&p 500 stocks based on the decoded information (also known as latent space) features we extract from the AE
Language:Python 4amangupta143 / Air-Quality-Prediction-FB-Prophet
This project focuses on time series forecasting of air quality data using the Facebook Prophet algorithm.
Language:Jupyter Notebook 3Kulshre142 / E-Commerce-Food-Product-Sales-Forcasting-System
This repository holds the project Food Products Sales Forecasting which includes data preparation, data visualization, and forecasting for sales of food products.
Language:HTML 3samiraat / forecasting-Singapore-PSI-pm2.5-2016-2019
forecasting time series Singapore PSI (pm2.5) 2016-2019
Language:Python 3ulkudilemre / Forecast-of-production-with-agricultural-data-of-Turkish-provinces
Bu projede TUİK ve Konya Belediye Açık Veri Platformundan alınan verilerle yapılmış 3 ayrı çalışma bulunmaktadır.
Language:Jupyter Notebook 3z76316 / CubePerturbMCF
AAAI 2021: A Multi-step-ahead Markov Conditional Forward Model with Cube Perturbations for Extreme Weather Forecasting
Language:Jupyter Notebook 330lm32 / ml-time-series-analysis-sarimax
Building different models for non-seasonal and seasonal approaches by using ARIMA and SARIMAX in statsmodels package, respectively.
Language:Jupyter Notebook 2aghezzafmohamed / Data-traffic-prediction
Forcasting the volume of DATA 2G, 3G and 4G stream
Language:Jupyter Notebook 2AmirFARES / Store-Sales-Forecasting
Sales forecasting for grocery stores using time series analysis and machine learning.
Language:Jupyter Notebook 2FirasMezghi / Tunisian_Stock_Index_Forecasting
Building a forecasting model to forescast stock index in Tunisia (TUNINDEX)
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geehaad / Time-Series_Different-models
understand Time series forecasting with different models in python, and fine tune the hyper-parameters to get the least possible error.
Language:Jupyter Notebook 2 HEMANGANI / Enrollment-Forecast
This project implements a machine learning forecast model using XGBoost to predict headcount based on historical data. The model preprocesses the data, trains on the training set, and generates predictions for the test set.
Language:Jupyter Notebook 2shakibyzn / London-bike-sharing-time-series-analysis
Multivariate time series analysis on london bike sharing dataset
Language:Jupyter Notebook 2soheshdoshi / ForcastModel
This Model is Base On Halt & Winter Algorithm.This Model is Forecast About Seasonal Data.
Language:Python 2tango911 / zs-ds-challenge-summer-2018-future-medical-events
The challenge was organized by zs on Hackerearth and it was open for US citizens. I scored 5th rank on leaderboard
Language:Jupyter Notebook 2VaibhavDongre1311 / End_to_end_oil_price_Forcasting_project
Business Problem: Oil price may fluctuate time to time based on more factors technical economical and natural as well as political so the forecasting may not be influenced by these some unexpected scenarios like Geopolitical issues (e.g.: War and Oil price Cap).
Language:Jupyter Notebook 2AliakbarMehdizadeh / RL-LSTM-Trader
This project involves developing and testing a trading model designed to predict stock prices and evaluate trading strategies. The core of the project includes building and training a LSTM based model for time series forecasting in addition to a RL model, evaluating its performance, and visualizing the results.
Language:Python 1lokesh9899 / Analysis-of-Global-Food-Agriculture-Statistics-for-Strategic-Insights
This project delves into various aspects of agricultural production across multiple countries, using three distinct datasets: Agriculture Production, Agriculture Land Use, and Climate Factors. The analysis aims to uncover trends, relationships, and improvements in crop yields, land use, and production indices.
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