Скачать или смотреть How I Adapted ChatGPT's Transformers Networks for Trading Prediction (Free Python Code)

In this video, I show you exactly how I adapted ChatGPT's inspired transformer networks for trading prediction using Python. You'll learn how to build your own AI trading system by applying the same neural networks architecture that powers ChatGPT to financial markets.

What You'll Learn:
How transformers work and why they're perfect for predictions
Step-by-step Python implementation of transformer networks for forex forecasting
How to train neural networks on EUR/USD historical data
Practical trading prediction techniques using AI transformers
Complete Python code walkthrough with PyTorch

*** How to deploy a live trading bot in python:
   • How To Build A Trading Bot In Python  

Key Topics Covered:
✅ Transformer networks architecture explained
✅ Adapting AI for financial markets
✅ Python trading prediction implementation
✅ Neural networks for forex forecasting
✅ PyTorch transformer model building
✅ AI trading strategies with Python code

This tutorial bridges the gap between natural language processing and quantitative finance, showing you how to leverage the same transformer networks that make ChatGPT so powerful for your own trading prediction systems.

Perfect for Python developers interested in AI trading, machine learning engineers exploring financial applications, and anyone curious about applying ChatGPT's technology to markets.

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📘 Book available on Amazon (Algorithmic Trading Hands-On Approach Using Python):
https://a.co/d/6woMBHt

💲 Algorithmic Trading Courses and Python for all levels (Udemy Sale Coupons):
https://www.codetradingcafe.com/

Happy learning, happy coding ☕
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Free Python Code, Download the complete source code and data here:
https://drive.google.com/drive/folder...

or from github:
https://github.com/ZiadFrancis/Transf...

Timestamps:
00:00 - Introduction to Transformers for Trading
01:07 - Understanding ChatGPT's Architecture
02:16 - Transformers applied to trading
03:50 - Setting up the environment
08:50 - Building the Transformer Network
12:20 - Training on EUR/USD Data
20:10 - Testing Trading Predictions

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