Deep Learning for Sentiment Analysis
The Deep Learning Model for Sentiment Analysis
Building a Model using Pre-Trained Word Embeddings
Wrap Up: Sentiment Analysis
Natural Language Processing with Code
Build a convolutional network for sentiment analysis, using Keras code in Dataiku’s Visual Machine Learning tool.
Binary Sentiment Analysis is the task of automatically analyzing a text data to decide whether it is positive or negative. This is useful when faced with a lot of text data that would be too time-consuming to manually label. In Dataiku you can build a convolutional neural network model for binary sentiment analysis.
This how-to walks through how to build a convolutional network for sentiment analysis, using Keras code in Dataiku’s Visual Machine Learning. After building an initial model, we’ll use pre-trained word embeddings to improve the preprocessing of inputs, and then evaluate both models on test data.