Yuqiang Pan / 발표
기고글
Tuning LLMs with Your Own Personalized Data and Integrating into EA (Part 5): Develop and Test Trading Strategy with LLMs(I)-Fine-tuning MetaTrader 5를 위하여
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to
Integrate Your Own LLM into EA (Part 4): Training Your Own LLM with GPU MetaTrader 5를 위하여
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to
Integrate Your Own LLM into EA (Part 3): Training Your Own LLM with CPU MetaTrader 5를 위하여
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to
Data label for time series mining (Part 6):Apply and Test in EA Using ONNX MetaTrader 5를 위하여
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy
Data label for time series mining (Part 5):Apply and Test in EA Using Socket MetaTrader 5를 위하여
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy
Data label for time series mining (Part 4):Interpretability Decomposition Using Label Data MetaTrader 5를 위하여
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy
Integrate Your Own LLM into EA (Part 2): Example of Environment Deployment MetaTrader 5를 위하여
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to
Integrate Your Own LLM into EA (Part 1): Hardware and Environment Deployment MetaTrader 5를 위하여
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to
Data label for time series mining (Part 3):Example for using label data MetaTrader 5를 위하여
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy
Data label for timeseries mining (Part 2):Make datasets with trend markers using Python MetaTrader 5를 위하여
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy