Cтатьи
Data Science and ML (Part 27): Convolutional Neural Networks (CNNs) in MetaTrader 5 Trading Bots — Are They Worth It? для MetaTrader 5
Convolutional Neural Networks (CNNs) are renowned for their prowess in detecting patterns in images and videos, with applications spanning diverse fields. In this article, we explore the potential of CNNs to identify valuable patterns in financial markets and generate effective trading signals for
Data Science and ML (Part 26): The Ultimate Battle in Time Series Forecasting — LSTM vs GRU Neural Networks для MetaTrader 5
In the previous article, we discussed a simple RNN which despite its inability to understand long-term dependencies in the data, was able to make a profitable strategy. In this article, we are discussing both the Long-Short Term Memory(LSTM) and the Gated Recurrent Unit(GRU). These two were
Data Science and Machine Learning (Part 25): Forex Timeseries Forecasting Using a Recurrent Neural Network (RNN) для MetaTrader 5
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
Data Science and Machine Learning (Part 24): Forex Time series Forecasting Using Regular AI Models для MetaTrader 5
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)
Data Science and Machine Learning (Part 23): Why LightGBM and XGBoost outperform a lot of AI models? для MetaTrader 5
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
Data Science and Machine Learning (Part 22): Leveraging Autoencoders Neural Networks for Smarter Trades by Moving from Noise to Signal для MetaTrader 5
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
Overcoming ONNX Integration Challenges для MetaTrader 5
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
Data Science and Machine Learning(Part 21): Unlocking Neural Networks, Optimization algorithms demystified для MetaTrader 5
Dive into the heart of neural networks as we demystify the optimization algorithms used inside the neural network. In this article, discover the key techniques that unlock the full potential of neural networks, propelling your models to new heights of accuracy and efficiency
Машинное обучение и Data Science (Часть 20): Выбор между LDA и PCA в задачах алготрейдинга на MQL5 для MetaTrader 5
В этой статье мы рассмотрим методы уменьшения размерности и их применение в торговой среде MQL5. В частности, мы изучим нюансы линейного дискриминантного анализа (LDA) и анализа главных компонентов (PCA), а также посмотрим на их влияние при разработке стратегий и анализе рынка
Машинное обучение и Data Science (Часть 19): Совершенствуем AI-модели с помощью AdaBoost для MetaTrader 5
Алгоритм AdaBoost используется для повышения производительности моделей искусственного интеллекта. AdaBoost (Adaptive Boosting, адаптивный бустинг) представляет собой сложную методику ансамблевого обучения, которая легко объединяет слабых учащихся, повышая их коллективную способность