Module 8- part 1- Deep Dive into Facebook Prophet: Paper Review – Helpful but Overhyped? скачать в хорошем качестве

Module 8- part 1- Deep Dive into Facebook Prophet: Paper Review – Helpful but Overhyped?

In this module, we explore Prophet and its extension NeuralProphet — powerful forecasting tools designed to tackle real-world business time series challenges. Developed by Facebook, Prophet is known for its ease of use, interpretability, and flexibility in modeling complex components like holidays, multiple seasonalities, and growth constraints. We then expand the scope by introducing NeuralProphet, which builds on Prophet by adding autoregressive modeling and a neural network component to capture short-term dependencies and richer dynamics. we do this module in 5 parts: 1- Facebook Prophet (Theory), (this video) 2- Prophet python basics 3- Prophet python advanced 4- NeuralProphet (Theory) 5- NeuralProphet (Python) Lecture timestamps: 0:00 prophet and neuralprophet intro (why we should go beyond prophet) 2:45 part 1- Facebook Prophet model. what is it? 28:52 Core components of prophet (growth/trend, seasonality, holiday) 34:25 Trend component 45:51 Seasonality component 52:28 Holiday component 57:05 Model fitting (MAP) 1:01:54 Analyst in the loop Relevant playlists: Deep Forecasting Concepts, simply explained:    • Deep Forecasting codes and concepts (Simpl...   Machine Learning Codes and Concepts:    • Machine Learning Codes and Concepts (Simpl...   Deep Learning Concepts, simply explained:    • Deep Learning Codes and Concepts (Simply E...   Instructor: Pedram Jahangiry All of the slides and notebooks used in this series are available on my GitHub page, so you can follow along and experiment with the code on your own. https://github.com/PJalgotrader