DL_for_NLP_Jason-Brownlee

Deep Learning for Natural Language Processing Repository

• Part 1: Foundations. Discover a gentle introduction to natural language processing, deep learning, and the promise of combining the two, as well as tutorials on how to get started with Keras.

• Part 2: Data Preparation: Discover tutorials that show how to clean, prepare and encode text ready for modeling with neural networks.

• Part 3: Bag-of-Words. Discover the bag-of-words model, a staple representation for machine learning and a good starting point for neural networks for sentiment analysis.

• Part 4: Word Embeddings. Discover a more powerful word representation in word embeddings, how to develop them as standalone models, and how to learn them as part of neural network models.

• Part 5: Text Classification. Discover how to leverage word embeddings and convolutional neural networks to learn spatial invariant models of text for sentiment analysis, a successor to the bag-of-words model.

• Part 6: Language Modeling. Discover how to develop character-based and word-based language models, a technique that is required as part of any modern text generating model.

• Part 7: Image Captioning. Discover how to combine a pre-trained object recognition model with a language model to automatically caption images.

• Part 8: Machine Translation. Discover how to combine two language models to automatically translate text from one language to another.