In this course, you will :
- Harshit Tyagi, the instructor, provides a comprehensive guide to understanding NLP using recurrent neural networks (RNNs).
- begins by introducing you to word encodings and tokenization with TensorFlow.
- describes the key concept of word embeddings and demonstrates how to use TensorFlow to classify movie reviews and project vectors
- RNNs and long short-term memory (LSTM) are discussed, and then you will see how to improve the movie review classifier from earlier in the course.
- concludes with an explanation of how to train RNNs to predict the next word in a sentence, allowing you to generate some original text.
1. Getting Started with NLP
- Introduction to natural language processing
- Introduction to word encodings
- Tokenization using TensorFlow
2. Text Classification
- Classifying movie reviews using TensorFlow
- Projecting vectors using TensorFlow
- Building a text classifier
3. Classification with RNNs and LSTMs
- Implementing LSTMs with TensorFlow
- Improving your movie review classifier
4. Text Generation with RNNs
- Predicting the next word