Neural networks made easy (Part 61): Optimism issue in offline reinforcement learning

Introduction Recently, offline reinforcement learning methods have become widespread, which promises many prospects in solving problems of varying complexity. However, one of the main problems that researchers face is the optimism that can arise while learning. The agent optimizes its strategy based on the data from the training set and gains confidence in its actions. […]

Integrating ML models with the Strategy Tester (Conclusion): Implementing a regression model for price prediction

Introduction: In the previous article, we completed the implementation of a CSV file management class for storing and retrieving data related to financial markets. Having created the infrastructure, we are now ready to use this data to build and train a machine learning model. Our task in this article is to implement a regression model that […]

Deep Learning GRU model with Python to ONNX with EA, and GRU vs LSTM models

Introduction This is the continuation of Deep Learning Forecast and Order Placement using Python, the MetaTrader5 Python package and an ONNX model file, but you continue this one without the previous one. All will be explained. Everything we will use is included in this article. In this section, we will guide you through the entire process, […]