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![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 25): Forex Timeseries Forecasting Using a Recurrent Neural Network (RNN)](https://c.mql5.com/2/82/Data_Science_and_ML_Part_25__LOGO.png)
Recurrent neural networks (RNNs) excel at leveraging past information to predict future events. Their remarkable predictive capabilities have been applied across various domains with great success. In this article, we will deploy RNN models to predict trends in the forex market, demonstrating their potential to enhance forecasting accuracy in forex trading.
![fxsaber](https://c.mql5.com/avatar/2019/8/5D67260D-44C9.png)
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 24): Forex Time series Forecasting Using Regular AI Models](https://c.mql5.com/2/81/Data_Science_and_Machine_Learning_Part_24__LOGO.png)
In the forex markets It is very challenging to predict the future trend without having an idea of the past, Very few machine learning models are capable of making the future predictions by considering past values. In this article, we are going to discuss how we can use classical(Non-time series) Artificial Intelligence models to beat the market
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 23): Why LightGBM and XGBoost outperform a lot of AI models?](https://c.mql5.com/2/79/Data_Science_and_ML_Part_23_____LOGO____2.png)
These advanced gradient-boosted decision tree techniques offer superior performance and flexibility, making them ideal for financial modeling and algorithmic trading. Learn how to leverage these tools to optimize your trading strategies, improve predictive accuracy, and gain a competitive edge in the financial markets.
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![Nikolai Semko - BeeXXI Corporation](https://c.mql5.com/avatar/2022/11/6383de4f-d007.jpg)
Сверхбыстрое распознание параболических каналов ( а также линейных, горизонтальных и волнообразных) на всей глубине истории, создавая иерархию каналов. Необходима настройка: Max bars in chart: Unlimited Данный индикатор предназначен в первую очередь для алгоритмического трейдинга, но можно использовать и для ручной торговли Льготная цена до 20 июля для друзей и для тех, у кого хорошая реакция Данный индикатор будет иметь в ближайшем будущем очень активную эволюцию и подробные
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Data Science and Machine Learning (Part 22): Leveraging Autoencoders Neural Networks for Smarter Trades by Moving from Noise to Signal](https://c.mql5.com/2/77/Data_Science_and_ML_gPart_22k_____LOGO.png)
In the fast-paced world of financial markets, separating meaningful signals from the noise is crucial for successful trading. By employing sophisticated neural network architectures, autoencoders excel at uncovering hidden patterns within market data, transforming noisy input into actionable insights. In this article, we explore how autoencoders are revolutionizing trading practices, offering traders a powerful tool to enhance decision-making and gain a competitive edge in today's dynamic markets.
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
![Overcoming ONNX Integration Challenges](https://c.mql5.com/2/75/Overcoming_ONNX_Integration_Challenges____LOGO.png)
ONNX is a great tool for integrating complex AI code between different platforms, it is a great tool that comes with some challenges that one must address to get the most out of it, In this article we discuss the common issues you might face and how to mitigate them.
![fxsaber](https://c.mql5.com/avatar/2019/8/5D67260D-44C9.png)
![MetaQuotes](https://c.mql5.com/avatar/2010/1/4B5DE8B4-9045.jpg)
![fxsaber](https://c.mql5.com/avatar/2019/8/5D67260D-44C9.png)
![Omega J Msigwa](https://c.mql5.com/avatar/2022/6/62B4B2F2-C377.png)
Индикатор линейной регрессии с искусственным интеллектом: Линейная регрессия — это простой, но эффективный метод искусственного интеллекта, который лежит в основе сложных нейронных сетей. Этот индикатор построен на основе анализа линейной регрессии и пытается делать прогнозы относительно предстоящего события на рынке. Входы: train_bars: контролирует количество баров, на которых информация о ценах будет собираться и использоваться для обучения ИИ внутри него. Чем больше это значение, тем лучше, а
![fxsaber](https://c.mql5.com/avatar/2019/8/5D67260D-44C9.png)