텍스트 분석 및 계산 금융
Deep Learning Toolbox™를 사용하여 텍스트 분석과 계산 금융 응용 분야에 딥러닝을 적용합니다.
추천 예제
딥러닝을 사용하여 텍스트 데이터 분류하기
이 예제에서는 딥러닝 장단기 기억(LSTM) 신경망을 사용하여 텍스트 데이터를 분류하는 방법을 보여줍니다.
Multilabel Text Classification Using Deep Learning
Classify text data that has multiple independent labels.
Sequence-to-Sequence Translation Using Attention
Convert decimal strings to Roman numerals using a recurrent sequence-to-sequence encoder-decoder model with attention.
Compare Deep Learning Networks for Credit Default Prediction
Create, train, and compare three deep learning networks for predicting credit default probability.
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.
Hedge Options Using Reinforcement Learning Toolbox
Outperform the traditional BSM approach using an optimal option hedging policy.
