- Lesson 01: Natural Language Processing
- Lesson 02: Deep Learning
- Lesson 03: Promise of Deep Learning for Natural Language
- Lesson 04: Now to Develop Deep Learning Models With Keras
- Lesson 05: How to Clean Text Manually and with NLTK
- Lesson 06: How to Prepare Text Data with scikit-learn
- Lesson 07: How to Prepare Text Data With Keras
- Lesson 08: The Bag-of-Words Model
- Lesson 09: Prepare Movie Review Data for Sentiment Analysis
- Lesson 10: Neural Bag-of-Words Model for Sentiment Analysis
- Lesson 11: The Word Embedding Model
- Lesson 12: How to Develop Word Embeddings with Gensim
- Lesson 13: How to Learn and Load Word Embeddings in Keras
- Lesson 14: Neural Models for Document Classification
- Lesson 15: Develop an Embedding + CNN Model
- Lesson 16: Develop an n-gram CNN Model for Sentiment Analysis
- Lesson 17: Neural Language Modeling
- Lesson 18: Develop a Character-Based Neural Language Model
- Lesson 19: How to Develop a Word-Based Neural Language Model
- Lesson 20: Develop a Neural Language Model for Text Generation
- Lesson 21: Neural Image Caption Generation
- Lesson 22: Neural Network Models for Caption Generation
- Lesson 23: Load and Use a Pre-Trained Object Recognition Model
- Lesson 24: How to Evaluate Generated Text With the BLEU Score
- Lesson 25: How to Prepare a Photo Caption Dataset For Modeling
- Lesson 26: Develop a Neural Image Caption Generation Model
- Lesson 27: Neural Machine Translation
- Lesson 28: Encoder-Decoder Models for NMT
- Lesson 29: Configure Encoder-Decoder Models for NMT
- Lesson 30: How to Develop a Neural Machine Translation Model
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