NeuralProphet: A simple forecasting package

Gold-Price-forecasting In a personal endevaour to learn about time series analysis and forecasting, I decided to reserach and explore various quantitative forecasting methods.This notebook documents contains the methods that can be applied to forecast gold price and model deployment using streamlit, along with a detailed explaination of the diff…

Predecitve model for Stock Return forecast (future prediction) for FTS100 Tech-Mark Series (top technical firms) in UK listed on London Stock Exchange

This repository contains an ML project that was approached with a business mindset from the beginning to the end. It addresses the problem of forecasting.

This repository is dedicated to the group project for the Time Series and Forecasting exam.

Built a model to predict the Sales of a store

A comparison of time-series forecasting models on a weekday-only data using StatsForecast library.

Forecasting is a technique that uses historical data as inputs to make informed estimates that are predictive in determining the direction of future trends. Businesses utilize forecasting to determine how to allocate their budgets or plan for anticipated expenses for an upcoming period of time

Forecasting using simple linear regression method, case study forecasting the number of visitors to a mall. Demo: https://kevinmalikfajar.alwaysdata.net/forecasting-regresi-linear-sederhana/

Analysis and forecasting monthly Atmospheric Carbon Dioxide Emissions from March, 1951 to December, 2021 Analysis and Computing done in R studio software

Forecasting sales and economic demand for businesses with a time series approach using NeuralProphet

Evaluation and review of various popular Auto Time Series Algorithms - Fbprophet, DART and PyCaret

Trying the Temporal Fusion Transformer model for forecasting Renewable energy.

Forecasting problem for Sales of a Plastic manufacturer

Machine Learning Competition by BUYAK

Graph Neural Networks utilization for Spatiotemporal graphs. These methods will be applied into the problem of forecasting traffic flow on PEMS-Bay, METR-LA and Seattle Loop Datasets

(finished) S1 Skripsi UGM | forecasting USD | RNN and UKF

Conducting Market Forecasting using Excel with different modeling algorithms.

Jupyter Notebooks Collection for Learning Time Series Models