Better NN EA development - page 87

[Sergey Golubev]

Forum on trading, automated trading systems and testing trading strategies

MetaTrader 5 Python User Group - the summary

Sergey Golubev, 2024.06.05 05:02

Data Science and ML (Part 23): Why LightGBM and XGBoost outperform a lot of AI models? 

Gradient Boosted Decision Trees (GBDT) are a powerful machine learning technique used primarily for regression and classification tasks. They combine the predictions of multiple weak learners, usually decision trees, to create a strong predictive model.

The core idea is to build models sequentially, each new model attempting to correct the errors made by the previous ones.

Have gained much popularity in the machine learning community as the algorithms of choice for many winning teams in machine learning competitions. In this article, we are going to discover how we can use these accurate models in our trading applications.

[Sergey Golubev]

Forum on trading, automated trading systems and testing trading strategies

MetaTrader 5 Python User Group - the summary

Sergey Golubev, 2024.06.25 12:35

Data Science and Machine Learning (Part 24): Forex Time series Forecasting Using Regular AI Models

Time series forecasting is the process of using past data to predict future values in a sequence of data points. This sequence is typically ordered by time, hence the name time series.

[Sergey Golubev]

Forum on trading, automated trading systems and testing trading strategies

MetaTrader 5 Python User Group - the summary

Sergey Golubev, 2024.07.06 15:10

Data Science and Machine Learning (Part 25): Forex Timeseries Forecasting Using a Recurrent Neural Network (RNN)

Recurrent Neural Networks (RNNs) are artificial neural networks designed to recognize patterns in sequences of data, such as time series, language, or video. Unlike traditional neural networks, which assume that inputs are independent of each other, RNNs can detect and understand patterns from a sequence of data (information).

A basic understanding of Python, ONNX in MQL5, and Python machine learning is required to understand the contents of this article fully.

[Sergey Golubev]

Forum on trading, automated trading systems and testing trading strategies

MetaTrader 5 Python User Group - the summary

Sergey Golubev, 2024.07.26 14:47

Data Science and ML (Part 26): The Ultimate Battle in Time Series Forecasting — LSTM vs GRU Neural Networks

Long Short-Term Memory(LSTM), is a type of recurrent neural network designed for sequence tasks, excelling in capturing and utilizing long-term dependencies in data. Unlike vanilla Recurrent Neural Networks(simple RNNs) discussed in the previous article of this series (a must-read). Which can't capture long-term dependencies in the data.

[Sergey Golubev]

Forum on trading, automated trading systems and testing trading strategies

MetaTrader 5 Python User Group - the summary

Sergey Golubev, 2024.07.26 14:50

Data Science and ML (Part 27): Convolutional Neural Networks (CNNs) in MetaTrader 5 Trading Bots — Are They Worth It?

Convolutional Neural Networks (CNNs) are a class of deep learning algorithms specifically designed to process structured grid-like data, such as images, audio spectrograms, and time-series data. They are particularly well-suited for visual data tasks because they can automatically and adaptively learn spatial hierarchies of features from input data.

CNNs are the extended version of artificial neural networks (ANN). They are predominantly used to extract the feature from the grid-like matrix dataset. For example, visual datasets like images or videos where data patterns play an extensive role.