Deep learning methods are achieving state-of-the-art results on challenging machine learning problems, such as describing photos and translating text from one language to another. In this new highly-focused course - written by developers, for developers – we’ll cut through the excess math, research papers and patchwork descriptions about natural language processing to deep dive into the technology in a meaningful, practical way to gain real world skills to leverage on the job right after the training ends.
This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course.In this course you learn about:· Neural Text Classification. Develop a deep learning model to classify the sentiment of movie reviews as either positive or negative.
· Neural Language Modeling. Develop a neural language model on the text of Plato in order to generate new tracts of text with the same style and flavor as the original.
· Neural Photo Captioning. Develop a model to automatically generate a concise description of ad hoc photographs.
· Neural Machine Translation. Develop a model to translate sentences of text in German to English.
· Neural Bag-of-Words. Develop neural network models that model text as a bag-of-words where word order is ignored.
· Neural Word Embedding. Develop neural network models that model text using a distributed representation.
· Embedding + CNN. Develop deep learning models that combine word embedding representations with convolutional neural networks.
· Encoder-Decoder RNN. Develop recurrent neural networks that use the encoder-decoder architecture.
- Natural Language Processing 00:00:00
- Deep Learning 00:00:00
- Promise of Deep Learning for Natural Language 00:00:00
- How to Clean Text Manually and with NLTK 00:00:00
- How to Prepare Text Data with scikit-learn 00:00:00
- How to Prepare Text Data with Keras 00:00:00
- Bag-of-Words 00:00:00
- The Bag-of-Words Model 00:00:00
- Prepare Movie Review Data for Sentiment Analysis 00:00:00
- Neural Bag-of-Words Model for Sentiment Analysis 00:00:00
- The Word Embedding Model 00:00:00
- How to Develop Word Embeddings with Gensim 00:00:00
- How to Learn and Load Word Embeddings in Keras 00:00:00
- Neural Language Modeling 00:00:00
- Develop a Character-Based Neural Language Model 00:00:00
- How to Develop a Word-Based Neural Language Model 00:00:00
- Develop a Neural Language Model for Text Generation 00:00:00
- Neural Machine Translation 00:00:00
- Encoder-Decoder Models for NMT 00:00:00
- Configure Encoder-Decoder Models for NMT 00:00:00
- How to Develop a Neural Machine Translation Model 00:00:00