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In this course, you will learn :
- To implement sentiment analysis, complete analogies, and translate words, use logistic regression, naive Bayes, and word vectors.
- To implement autocorrect, autocomplete, and identify part-of-speech tags for words, use dynamic programming, hidden Markov models, and word embeddings.
- Trax supports sentiment analysis, text generation, and named entity recognition using recurrent neural networks, LSTMs, GRUs, and Siamese networks.
- To machine translate complete sentences, summarise text, build chatbots, and answer questions, use encoder-decoder, causal, and self-attention.
Syllabus :
- Natural Language Processing with Classification and Vector Spaces
- Natural Language Processing with Probabilistic Models
- Natural Language Processing with Sequence Models
- Natural Language Processing with Attention Models
