Natural-Language-Processing-Specialization

Main topics and Projects worked in this specialization.

Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies & translate words.
Use dynamic programming, hidden Markov models, and word embeddings to implement autocorrect, autocomplete & identify part-of-speech tags for words.
Use recurrent neural networks, LSTMs, GRUs & Siamese network in TensorFlow & Trax for sentiment analysis, text generation & named entity recognition.
Use encoder-decoder, causal, & self-attention to machine translate complete sentences, summarize text, build chatbots & question-answering.

Name		Name	Last commit message	Last commit date
Latest commit History 16 Commits
NLP with Attention Models		NLP with Attention Models
NLP with Classification-vector-spaces		NLP with Classification-vector-spaces
NLP with Probablistic Models		NLP with Probablistic Models
NLP with Sequence Models		NLP with Sequence Models
Coursera UYWKSAX6JT8G.pdf		Coursera UYWKSAX6JT8G.pdf
LICENSE		LICENSE
README.md		README.md
natural-language-processing formula sheet.pdf		natural-language-processing formula sheet.pdf