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  1. Neural networks made easy (Part 37): Sparse Attention

    by , 02-26-2024 at 04:19 AM
    In the previous article, we discussed relational models which use attention mechanisms in their architecture. We used this model to create an Expert Advisor, and the resulting EA showed good results. However, we noticed that the model's learning rate was lower compared to our earlier experiments. This is due to the fact that the transformer block used in the model is a rather complex architectural solution performing a large number of operations. The number of these operations grows in a quadratic
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  2. MQL5 Wizard Techniques you should know (Part 12): Newton Polynomial

    by , 02-23-2024 at 05:50 AM
    Time series analysis plays an important role not just in supporting fundamental analysis but in very liquid markets like forex, it can be the main driver for decisions on how one is positioned in the markets. Traditional technical indicators have tended to lag the market a lot which has brought them out of favor for most traders, leading to the rise of alternatives perhaps the most predominant of which, at the moment is neural networks. But what about polynomial interpolation?
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  3. Data label for time series mining(Part 1)

    by , 02-19-2024 at 04:19 AM
    When we design artificial intelligence models, we often need to prepare data first. Good data quality will allow us to get twice the result with half the effort in model training and validation. But our foreign exchange or stock data is special, which contains complex market information and time information, and data labeling is difficult, but we can easily analyze the trend in historical data on the chart.

    This section introduces a method of making data sets with trend marks by EA
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  4. Ready-made templates for including indicators to Expert Advisors (Part 2): Volume and Bill Williams indicators

    by , 02-10-2024 at 07:10 AM
    The article continues the topic of ready-made templates for using indicators in EAs. Here we will look at connecting to EAs and using volume and Bill Williams' indicators. We will display the data received from indicators on the dashboard created in the first article of this series. The panel has also been improved. At the end of the article, we will briefly look at its changes and improvements.
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  5. Wrapping ONNX models in classes

    by , 02-10-2024 at 04:19 AM
    In the previous article, we used two ONNX models to arrange the voting classifier. The entire source text was organized as a single MQ5 file. The entire code was divided into functions. But what if we try to swap models? Or add another model? The original text will become even bigger. Let's try the object-oriented approach.
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