Text Analytics and Computational Finance

Extend deep learning workflows with text analytics and computational finance applications

Use Deep Learning Toolbox™ to incorporate deep learning in text analytics and computational finance applications.

Featured Examples

Classify Text Data Using Deep Learning

Classify text data using a deep learning long short-term memory (LSTM) network.

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Multilabel Text Classification Using Deep Learning

Classify text data that has multiple independent labels.

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Sequence-to-Sequence Translation Using Attention

Convert decimal strings to Roman numerals using a recurrent sequence-to-sequence encoder-decoder model with attention.

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Compare Deep Learning Networks for Credit Default Prediction

Create, train, and compare three deep learning networks for predicting credit default probability.

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Interpret and Stress-Test Deep Learning Networks for Probability of Default

Train a credit risk for probability of default (PD) prediction using a deep neural network. The example also shows how to use the locally interpretable model-agnostic explanations (LIME) and Shapley values interpretability techniques to understand the predictions of the model. In addition, the example analyzes model predictions for out-of-sample values and performs a stress-testing analysis.

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Hedge Options Using Reinforcement Learning Toolbox

Outperform the traditional BSM approach using an optimal option hedging policy.

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