Generating labels for customer reviews (sentiment analysis)

Customer reviews are a goldmine of information for businesses. Analyzing sentiment in customer reviews helps in understanding customer satisfaction, identifying areas for improvement, and making data-driven business decisions.

In the following example, we delve into sentiment analysis using a neural network model. The code utilizes TensorFlow and Keras to create a simple neural network architecture with an embedding layer, a flatten layer, and a dense layer. The model is trained on a small labeled dataset for sentiment classification, distinguishing between positive and negative sentiments. Following training, the model is employed to classify new sentences. The provided Python code demonstrates each step, from tokenizing and padding sequences to compiling, training, and making predictions.

The following dataset is used for training on sentiment analysis:

sentences = ["I love this movie", "This movie...