Natural Language Processing with Sequence Models

Natural Language Processing with Sequence Models

Natural Language Processing with Sequence Models This course is part of Natural Language Processing Specialization Taught in English 22 languages available Some content may not be translated Instructors: Younes Bensouda Mourri +2 more Close Instructors Instructor ratings We asked all learners to give feedback on our instructors based on the quality of their teaching style.

Description

Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and humans using natural language. One of the key techniques in NLP is the use of sequence models, which allow machines to understand and generate human language in a more coherent and structured way.

Sequence models are a type of machine learning model that is designed to work with sequences of data, such as sentences or paragraphs. These models are particularly useful for tasks like language translation, speech recognition, and sentiment analysis, where the order of the words in a sentence is crucial to understanding its meaning.

One popular type of sequence model used in NLP is the recurrent neural network (RNN). RNNs are designed to process sequences of data one element at a time, with each element depending on the previous one

Natural Language Processing with Sequence Models

This course is part of Natural Language Processing Specialization

Taught in English

Some content may not be translated

Younes Bensouda Mourri
Łukasz Kaiser
Eddy Shyu

Instructors: Younes Bensouda Mourri

64,374 already enrolled

Course

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Intermediate level

Recommended experience

21 hours (approximately)
Flexible schedule
Learn at your own pace

What you’ll learn

  • Use recurrent neural networks, LSTMs, GRUs & Siamese networks in Trax for sentiment analysis, text generation & named entity recognition.

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Assessments

3 quizzes

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