Tesseract: Stock Market Forecasting 📈 Engine with JavaFX, Alpaca Trading and Facebook Prophet 💸 to analyze, forecast and trade stocks.
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Updated
Nov 1, 2023 - Java
Tesseract: Stock Market Forecasting 📈 Engine with JavaFX, Alpaca Trading and Facebook Prophet 💸 to analyze, forecast and trade stocks.
PREDICTING CRIME RATE IN CHICAGO USING FACEBOOK PROPHET
Prediction of future sales with fbprophet
Predictive algorithm for forecasting the mexican stock exchange. Machine Learning approach to forecast price and Indicator behaviours of MACD, Bollinger and SuperTrend strategy
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 The Future Using Facebook's Unsupervised Learning Machine Learning Procedure Prophet
Predicting stocks using Facebook prophet. for some big tech companies (TSLA, GOOG ,MSFT, FB, AAPL, NVDA, PYPL, ADBE, NFLX )
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.
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
Data Science web application for automated forecasting of univariate time-series data using Facebook Prophet on Python-Streamlit.
Exponential Smoothing, SARIMA, Facebook Prophet
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
Blent oil price forcast using Facebook Prophet
Preciting avocado prices using Facebook Prophet
📈 My solution to Kaggle's "Web Traffic Time Series Forecasting" competition, which uses Facebook's Prophet library to make predictions
Honours Dissertation Resources
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