Prediction of road casualties and evaluate the impact of transformations in Time Series Modeling and Forecasting with ARIMA using the R programming language

BitPredictor - A cutting-edge machine learning-based solution for predicting cryptocurrency prices. Harnessing the power of advanced algorithms and data analysis techniques, this system aims to provide accurate and timely forecasts for Bitcoin and other cryptocurrencies.

LSTM-ARIMA with Attention and Multiplicative Decomposition for Sophisticated Stock Forecasting.

Time Series Analysis of Covid-19 Dataset

Advanced stock market view

A forecasting system for multiple sectors that uses ARIMA, ETS, SVR, and other models displayed on a user friendly interface with different viewing options.

Rust library for time series modelling and forecasting

This project aims to develop a model using ARIMA & Seasonal ARIMA to forecast future sales

This repository contains Python functions for predicting time series.

Forecasting BTC Prices with a Linear Model (Linear Regression), Non-Linear Model (Non-Linear SVM), and ARIMA Model.

Prediccion de Criptomonedas BTC,ETH,ADA utilizando modelos RandomForest y ARIMA.

stock price analyst and predict its future by various model

The "Cincinnati Traffic Crashes - Time Series Analysis" is a comprehensive study that employs statistical techniques to examine patterns and trends in traffic accidents over time within the Cincinnati area. This analysis aims to forecast future incidents, and assist in developing strategies to enhance road safety.

Trabajo Presentado en el Máster de Big Data, Data Science e IA del tema de Series Temporales

Forecasting

Data Science project for forecasting steel and crude oil prices

This Python script conducts various data processing, visualization, and modeling tasks on a dataset.

Content: Unsupervised ML, Time Series analysis, Exponential Smoothing, Single Exponential smoothing, Holt Model, Holt Winter model, ARIMA model

A time series model to predict weekly sales of Walmart data consisting of 45 stores located in different regions including store information and monthly sales using ARIMA and Exponential Smoothing.

Time series data, prevalent across diverse domains like economics, finance, meteorology, and science, encompasses various phenomena such as daily sales, stock prices, temperatures, and population growth. We will analyze different datasets to discern patterns and forecast future trends or extract pertinent insights.