Neural Networks for Algorithmic Trading with MQL5
Dmitriy GizlykThe book has 7 chapters that cover everything you need to know to get started with neural networks and integrate them into your trading robots in MQL5. Beginning with basic principles of neural networks and advancing to more complex architectural solutions and attention mechanisms, this book provides all the necessary information for the successful implementation of machine learning in your algorithmic trading solutions.
You will discover how to use different types of neural networks, including convolutional and recurrent models, and how to integrate them into the MQL5 environment. Additionally, the book explores architectural solutions to improve model convergence, such as Batch Normalization and Dropout.
Furthermore, the author provides practical guidance on how to train neural networks and embed them into your trading strategies. You will learn how to create trading Expert Advisors to test the performance of trained models on new data, enabling you to evaluate their potential in real-world financial markets.