Deep Neural Networks (DNNs) Research
Machines emulating the functioning of the human brain.
aiquants Research
Perspective
Deep neural networks (DNNs) try to emulate the functioning of the human brain. They are composed of an input layer (the features), an output layer (the labels), and a number of hidden layers. It is this presence of hidden layers that makes a neural network deep, enabling it to learn and model a complex algorithmic trading strategy.

When applying DNNs, one generally speaks of deep learning instead of machine learning, a common nomenclature in the industry. They are considered the most powerful tools in the field.

Areas of research interest
  • DNNs with scikit-learn
  • DNNs with TensorFlow
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Our solutions
AI consulting
Python and its ecosystem of powerful packages is the technology platform of choice for algorithmic trading.

ML consulting
In recent years, we have seen how machine learning has gained popularity in solving traditional business problems.

DNNs (Deep Neural Networks)
[T]hey were silly enough to think you can look at the past to predict the future, The Economist.