Lazy Trading Part 7: Developing self-adapting Trading System

Learn to assemble Smart Self Learning Algorithms. Predict future price change based on financial data patterns

Created by: Vladimir Zhbanko
Senior Engineering Specialist and Instructor

Created by: Miguel Ferraz
Economist/Programmer

What Will I Learn?

• Log data from financial assets to files
• Learn to use Deep Learning with H2O
• Setup Automated Decision Support Loop
• Automate R scripts
• Develop R code
• Use Version control for your R project
• Writing R functions
• Perform data manipulations with pipes
• Use H2O Machine Learning platform in R
• Perform Deep Learning on Time-Series data
• Evaluate performance of Deep Learning models
• Backtest trading strategy in R Software

Requirements

• You should have a background knowledge on Trading and it's pitfals
• You want to learn Data Science using Trading
• PC Windows (min 4CPU 8Gb RAM). This machine should be left ON continuously for several weeks [Mac only with provided sample data]
• Java installation on Computer
• R Statistical Software
• R-Studio
• MT4 Trading Platform, Demo Trading Account
• GitHub Desktop Software for Version Control
• GitHub Account for Version Control

Target audience

• Anyone who want to be more productive
• Anyone who want to learn Data Science using Algorithmic Trading
• Anyone who want to try Algorithmic Trading but have little time
• Anyone willing to learn Deep Learning and understand how to apply it to make predictions