engineering

After the distributed representation has been obtained, the After the distributed representation is obtained, machine learning can be used to classify it. Models that can be used include Decision Tree SVM Support Vector Machine NN Neural Networks and others. SVM is included in NN in a broad sense. In this section, we will use the decision tree method. Bagging Image of majority voting with multiple decision trees Simple theory Decision trees are highly explainable and are a classic machine learning model. [Read More]

BART is a model for document summarization Derived from the same transformer as BERT Unlike BERT, it has an encoder-decoder structure This is because it is intended for sentence generation This page shows the steps to run a tutorial on BART. Procedure install transformers Run ``sh pip install transformers Run summary 2. Run the summary from transformers import BartTokenizer, BartForConditionalGeneration, BartConfig model = BartForConditionalGeneration.from_pretrained('facebook/bart-large') tokenizer = BartTokenizer.from_pretrained('facebook/bart-large') ARTICLE_TO_SUMMARIZE = "My friends are cool but they eat too many carbs. [Read More]

. We have successfully trained a model to automatically generate titles from news texts using a machine translation model based on deep learning. Preliminaries In the past, I was involved in a project to automatically generate titles from manuscripts for online news. In the past, I was involved in a project to automatically generate titles from manuscripts for online news. In order to tackle this project, I was looking into existing methods. [Read More]