Description

In Course 2 of the Natural Language Processing Specialization, you will:

a) Create a simple auto-correct algorithm using minimum edit distance and dynamic programming,
b) Apply the Viterbi Algorithm for part-of-speech (POS) tagging, which is vital for computational linguistics,
c) Write a better auto-complete algorithm using an N-gram language model, and
d) Write your own Word2Vec model that uses a neural network to compute word embeddings using a continuous bag-of-words model.Read more.

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Learning Sequence

Natural Language Processing with Probabilistic Models is a part of one structured learning path.

Coursera

DeepLearning.AI

4 Courses 4 Months

Natural Language Processing

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