Deep Learning with Python (Video 17)

The video tutorial covers sentiment analysis using a recurrent neural network with Keras. It begins with an introduction to sentiment analysis, highlighting the importance of understanding context. The IMDB movie review dataset is used for training, with preprocessing steps explained. The tutorial then delves into setting up word embeddings and the model architecture, including LSTM layers. Training and evaluation processes are discussed, achieving an accuracy of 82%. The video concludes with a comparison of recurrent and convolutional layers and hints at future challenges in deep learning.

What role does the LSTM layer play in the recurrent neural network model?

Explain how the model's output is bounded between zero and one.

What are the advantages of using recurrent neural networks over convolutional neural networks as mentioned in the video?