This project analyzes daily Covid-19 data for Indian states using SARIMAX models. It preprocesses data, checks stationarity, applies differencing, analyzes autocorrelation, selects SARIMAX parameters, conducts diagnostics, and forecasts cases. Dynamic forecasting's impact is limited.

Time series analysis and forecasting project based on Walmart Sales Data.

implementation forecasting model on thailand co2 emission datasets

Shell_App is an integrated data analysis and modeling platform, featuring scripts for EDA, ensemble techniques, LightGBM, and SARIMAX modeling. Designed for comprehensive data processing, the repository also includes deployment capabilities via Streamlit for interactive model interactions.

The Project uses a Kaggle Dataset that utilises information of UK's historical inflation rise and predict the inflation rate using SARIMA modelling.

This was a competition hosted by Zindi, about predicting the percent of areas burned by wildfires in Zimbabwe. This project emerged the winner.

Elevating Times Series Forecasting of Cars, Truck Sales in UK for precise and competitive forecasting in diverse industries.

Time series analysis using AR, ARIMA, SARIMAX on monthly Beer production by Austrian company.

Analyzing and predicting the stock prices,multiple machine learning models, including LSTM (Long Short-Term Memory), Prophet, and others

Demonstration of time series analysis using various concepts and models.

This project delves into the world of craft beer, analyzing and forecasting monthly beer production trends. It utilizes various time series analysis techniques to uncover patterns and predict future production levels.

Using time series modeling to forecast the top 3 zipcodes to invest in Washington state.

Predicting orders for Glovo

In this section, we will estimate airline passengers using time series methods.

This project aims to analyze and forecast the total funding amounts of startups using various regression and time series modeling techniques. Initially, we preprocess the dataset, which includes features such as funding amounts, company size, and number of funding rounds. The data is then scaled and split into training and testing sets.

Time Series Analysis of Airline Passenger Data, In this time series forecasting, taking data from kaggle site and applying ARIMA and SARIMAX model to evaluate seasional trends of passenger travelling via airlines.

To develop a robust climate change forecasting model using SARIMAX to predict temperature fluctuations, aiming to improve forecast accuracy by minimizing prediction errors.

Top-Down Investment Strategy Optimization with Time Series Forecasting

This project uses time series forecasting to predict future milk production. The data used in this project is monthly milk production data from January 1962 to December 1975. The ARIMA (autoregressive integrated moving average) model is used to forecast the milk production. The model is evaluated using various metric.