Forecasting footsteps in Walmart from previous years available timeseries data and predict on new years data.

Final Data Science group project for Henry Bootcamp. Developed data solutions for Olist, an ecommerce brazilian startup, including a Dashboard in PowerBI, a forecasting model deployed on Streamlit and a web app for remote access.

Predict stock prices using neural networks trained on historical price data.

This project enhances agricultural weather forecasting by predicting solar radiation (SRAD) using machine learning and deep learning models, including KNN, Random Forest, XGBoost, LSTM, and hybrid methods like Voting and Stacking Regressors.

Random Forest algorithm to forecast the hourly power generation of PV plant over time, using time series data and multiple features.

replication code and data for missing data, speculative reading article

This repo consist of predicting Air quality values like relative humidity, absolute humidity or any other features I have used forecasting method to analyze and predict

Predicting future stock prices based on past close prices and sentiment provided by a series of tweets. A time series forecasting survey using sentiment analysis.

ISI Summer Internship

Time Series Forecasting In R

This Kaggle competition challenges participants to use a modified version of the POWER NASA Temperature Dataset to build forecasting models.

Forecasting the Energy Load Consumption using time series data

Time series forecasting using ML models (ARIMA, SARIMA, SARIMAX and Prophet)

Statistical evaluation of renewable and non-renewable electricity generation in the EU.

Joy Store Sales Dashboard & Report using Power BI

Developing an accurate and reliable financial prediction model for the next 5 years using historical data, to assist investors, traders, and financial analysts make informed decisions about buying or selling stocks in a dynamic market.

Provide exploratory data analysis of the water level dataset from the Three Gorges dam in China as well as develop a machine learning model to forecast upstream water levels.

Real-time CO2 emissions data extraction, cleaning, preprocessing, and time series modeling (AR, ARIMA, SARIMA, LSTM). Analyze, select best model, and forecast CO2 emissions for 10 years. Comprehensive guide for CO2 forecasting using time series modeling.

How does user aggregate purchasing history and hotel prices affect number of nights stay at hotel over the weekend? Interested in the relationship between hotel price and search criteria of customers.

Apple revenue forecast