Natural Language Processing with TensorFlow

Introduction: Applications of LSTMs—Generating Text

Explore how to apply LSTMs and GRUs to generate text by training on character-level bigrams with embeddings. Understand language modeling for NLP and techniques like beam search to enhance text quality.

We'll cover the following...

Writing folk stories with LSTMs
Flow of the topics

1.Introduction to Natural Language Processing

2.Understanding TensorFlow 2

3.Word2vec: Learning Word Embeddings

4. Advanced Word Vector Algorithms

5.Sentence Classification with Convolutional Neural Networks

6.Recurrent Neural Networks

7.Understanding Long Short-Term Memory Networks

8.Applications of LSTM: Generating Text

9.Sequence-to-Sequence Learning: Neural Machine Translation

10.Transformers

Project

11.Image Captioning with Transformers

12.Final Remarks

13.Appendix: Mathematical Foundations and Advanced TensorFlow

Mock Interview

Introduction: Applications of LSTMs—Generating Text