Examples from the book "Neural Networks for Algorithmic Trading with MQL5" - MetaTrader 5 Expert

This book has 7 chapters and covers everything you need to know to start using neural networks and integrating them into your MQL5 trading robot. With easy-to-understand explanations, you'll learn the basics of machine learning and discover different types of neural networks, including convolutional and recurrent models, as well as more complex architectural solutions and attention mechanisms.

To help you integrate these solutions into your trading robot in the MQL5 environment, this book provides a large number of practical examples. In addition, the book explores various methods to improve model convergence, such as batch normalization and dropout.

Additionally, the authors provide practical guidance on how to train neural networks and embed them into your trading strategy. You will learn how to create trading Expert Advisors to test the performance of trained models on new data, allowing you to evaluate their potential in real-world financial markets.

"Neural Networks for Algorithmic Trading with MQL5" is more than just a book: it is a handy guide that can help you integrate advanced decision-making techniques into your trading algorithms and potentially improve financial performance. Start learning the advanced features of machine learning today and take your trading to the next level.

Attachment download

📎ea_template.mq5 (14.59 KB)

📎 activations.mqh (12.64 KB)

📎 activations.py (2.24 KB)

📎mult_vect_ocl.cl (3.38 KB)

📎mult_vect_ocl.mqh (8.09 KB)

📎 activation.mqh (57 KB)

📎 arraylayers.mqh (13.92 KB)

📎 buffer.mqh (36.65 KB)

📎 defines.mqh (32.59 KB)

📎 layerdescription.mqh (8.53 KB)

📎 lossfunction_.mqh (8.36 KB)

📎 neuronattention.mqh (48.33 KB)

📎 neuronbase.mqh (82.9 KB)

📎 neuronbatchnorm.mqh (31.42 KB)

📎 neuronconv.mqh (37.43 KB)

📎 neurondropout.mqh (22.88 KB)

📎 neurongpt.mqh (67.52 KB)

📎 neuronlstm.mqh (56.07 KB)

📎 neuronmhattention.mqh (42.97 KB)

📎neuronnet.mqh (64.88 KB)

📎 neuronproof.mqh (29.8 KB)

📎 opencl.mqh (20.19 KB)

📎 opencl_program.cl (113.76 KB)

📎 positionencoder.mqh (8.68 KB)

📎 attention.py (30.56 KB)

📎 attention_test.mq5 (21.34 KB)

📎 attention_test2.mq5 (21.39 KB)

📎batch_norm.py (23.79 KB)

📎 perceptron_test_norm.mq5 (21.43 KB)

📎check_gradient_conv.mq5 (20.85 KB)

📎 convolution.py (20.19 KB)

📎 convolution_test.mq5 (22.52 KB)

📎 convolution_test2.mq5 (23.29 KB)

📎 convolution_test3.mq5 (22.5 KB)

📎 dropout.py (37.58 KB)

📎 gpt_test.mq5 (22.29 KB)

📎 gpt_test_not_norm.mq5 (27.5 KB)

📎create_initial_data.mq5 (16.34 KB)

📎 initial_data.mq5 (16.62 KB)

📎 initial_data_macd.mq5 (10.1 KB)

📎 initial_data_macd_pow.mq5 (13.22 KB)

📎 initial_data_macd_shift.mq5 (9.9 KB)

📎 initial_data_rsi.mq5 (11.8 KB)

📎 initial_data_rsi_pow.mq5 (9.92 KB)

📎 initial_data_rsi_shift.mq5 (9.47 KB)

📎 opencl_test.mq5 (6.65 KB)

📎 template.py (9.03 KB)

📎 check_gradient_percp.mq5 (17.91 KB)

📎 perceptron.py (19.39 KB)

📎 perceptron_test.mq5 (19.87 KB)

📎check_gradient_lstm.mq5 (15.29 KB)

📎 lstm.py (27.64 KB)

📎 lstm_test.mq5 (21.07 KB)

Source: MQL5 #48097