
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Building artificial intelligence in MetaQuotes involves developing algorithms that can learn from data and make predictions or decisions based on that data. In order to build AI in MetaQuotes, you will need to have a solid understanding of machine learning, programming, and the MetaQuotes platform. First, we need to define the problem that we want to solve. For example, we might want to use historical data to predict the price of a particular financial instrument. To do this, we will use a machine learning algorithm called a neural network. Here's an example of how to build a neural network in Python using the Keras library:
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) model.fit(X_train, y_train, epochs=50, batch_size=32,validation_data=(X_test, y_test))
Here is the complete example: