Cách tôi điều chỉnh Mạng lưới Transformers của ChatGPT để Dự đoán Giao dịch (Mã Python Miễn phí)

Nguồn: https://www.youtube.com/watch?v=TT_D-4z-4zY

Tác giả: CodeTrading

Ngày xuất bản: 2025-06-05T00:00:00

Length: 23:46

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:

https://youtu.be/WcfKaZL4vpA

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.

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

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Discount Vouchers for my Algorithmic Trading courses:

💲 Algorithmic Trading: https://bit.ly/CouponAlgorithmicTrading

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Other beginners courses are linked in the About section of this channel, happy learning !

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Free Python Code, Download the complete source code and data here:

https://drive.google.com/drive/folders/1lUE_nvsNN91r7YOKsP4LJ_nGNprG4Uh-?usp=sharing

or from github:

https://github.com/ZiadFrancis/Transformers_Trading_01/tree/main