Predictive algorithm for forecasting the mexican stock exchange. Machine Learning approach to forecast price and Indicator behaviours of MACD, Bollinger and SuperTrend strategy

Exponential Smoothing, SARIMA, Facebook Prophet

📈 My solution to Kaggle's "Web Traffic Time Series Forecasting" competition, which uses Facebook's Prophet library to make predictions

Time series forecasting is a technique for the prediction of events through a sequence of time. Time-series forecasting decomposes the historical data into the baseline, trend, and seasonality. When a forecasting model doesn’t run as planned, we want to tune the parameters of the method with regards to the specific problem at hand. Tuning these …

Kaggle - Time-series Forecasting the optimal number of agents for a Contact Center: Facebook Prophet, InfluxDB Holt-Winter

Predicting stocks using Facebook prophet. for some big tech companies (TSLA, GOOG ,MSFT, FB, AAPL, NVDA, PYPL, ADBE, NFLX )

Data Science web application for automated forecasting of univariate time-series data using Facebook Prophet on Python-Streamlit.

Time series analysis showing trend, seasonality, and periodicity decomposition; and forecasting using Facebook Prophet. The analysis makes extensive use of indexing data tools and of the Pandas and Datetime libraries.

Tesseract: Stock Market Forecasting 📈 Engine with JavaFX, Alpaca Trading and Facebook Prophet 💸 to analyze, forecast and trade stocks.

This repository is created just for learning purpose, here we are going to implement various supervised machine algorithms based on the data to predict the target variable.

Time Series Using ARIMA and Facebook Prophet

Unemployment Rate Forecasting using Time Series techniques, leveraging Statsmodels, LSTMs, and Facebook's Prophet library to predict future unemployment trends. The project includes model comparison, hyperparameter tuning, and visualization of forecasted results.

Prediction of future sales with fbprophet

Utilized facebook prophet to perform forecasting on datasets that consist sales data from 1115 stores. Our predictive model attempts at forecasting future sales based on historical data while taking into account seasonality effects, demand, holidays, promotions, and competition.

PREDICTING CRIME RATE IN CHICAGO USING FACEBOOK PROPHET

Industrial Production Index Time Series Forecasting using a range of models including Holt-Winters, ARIMA, SARIMA, LSTMs, and Facebook's Prophet. The project focuses on predicting production trends through model evaluation, tuning, and visualization of forecasted outcomes.

Honours Dissertation Resources

Preciting avocado prices using Facebook Prophet

time series forecasting using Facebook prophet.