Module 6- part 3- A simple Deep Neural Network for timeseries forecasting in Python with Tensorflow скачать в хорошем качестве

Module 6- part 3- A simple Deep Neural Network for timeseries forecasting in Python with Tensorflow

In this module, we will delve into fundamental concepts in deep learning for timeseries forecasting. we do this module in 3 parts: 1- Neural Network basics for timeseries forecasting 2- Deep Learning regularization and going beyond DNN for timeseries forecasting 3- DNN for timeseries forecasting in Python (this video) Lecture timestamps: 00:00:00 Roadmap and recap (where to find the materials) 00:01:55 Pre-req (follow these steps if you have not familiar with Tensorflow) 00:03:53 the intuition notebook (what is happening behind the scene of a DNN for timeseries) 00:33:46 Univariate timeseries forecasting with DNN 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