This is a course specialization offered in Coursera.
Natural Language Processing (NLP) is a branch of artificial intelligence that uses algorithms allowing computers to interpret human speech or text.
This specialization focuses on the state-of-the-art deep learning techniques such as:
-
Logistic regression, Naïve Bayes and Word Vectors
- To implement sentiment analysis, complete analogies, translate words, and use locality-sensitive hashing to approximate nearest neighbors.
-
Dynamic Programming, Hidden Markov Models and word embeddings
- To autocorrect misspelled words, autocomplete partial sentences, and identify part-of-speech tags for words.
-
Dense and Recurrent Neural Networks, LSTMs, GRUs and Siamese Networks
- Used TensorFlow and Trax to perform advanced sentiment analysis, text generation, named entity recognition, and to identify duplicate questions.
-
Encoder-decoder, Causal and Self-attention
- To perform advanced machine translation of complete sentences, text summarization, question-answering, and to build chatbots.