Deep Learning for Price Action Prediction Using Databricks and AWS

Explore deep learning techniques for enhancing price action predictions using Databricks and AWS in this 36-minute video presentation. Discover how applying machine learning to traditional technical indicators can yield better results than raw price movements. Learn to use Databricks analysis tools and Amazon SageMaker for deep learning training to improve predictive capabilities of MACD and Slow stochastics indicators. Follow along as the presenters demonstrate building indicators in Databricks notebooks and extending functionality to train deep learning models in the cloud using PySpark and Amazon SageMaker. Gain insights into optimizing statistical parameters of indicators and hyperparameter tuning for the deepAR model, using the S&P 500 as a baseline. Suitable for beginners, this session covers topics including EMAs, sentiment changes, historical price action, stochastic strategy, reference architecture, prerequisites, and code walkthroughs, concluding with chart analysis and a summary.

Introduction
Presentation
Bull vs Bear
EMAs
When Sentiment Changed
Historical Price Action
Stochastic
Strategy
Deep AR
Reference Architecture
Prerequisites
Code Walkthrough
Chart Analysis
Summary