DeepLearning.AI
Natural Language Processing Specialization
DeepLearning.AI

Natural Language Processing Specialization

Break into NLP. Master cutting-edge NLP techniques through four hands-on courses! Updated with TensorFlow labs in December 2023.

Eddy Shyu
Łukasz Kaiser
Younes Bensouda Mourri

Instructors: Eddy Shyu

Sponsored by Coursera Learning Team

140,091 already enrolled

Get in-depth knowledge of a subject
4.6

(5,691 reviews)

Intermediate level

Recommended experience

3 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.6

(5,691 reviews)

Intermediate level

Recommended experience

3 months
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • 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 networks for sentiment analysis, text generation & named entity recognition.

  • Use encoder-decoder, causal, & self-attention to machine translate complete sentences, summarize text, and answer questions.

Details to know

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Taught in English

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Specialization - 4 course series

What you'll learn

  • Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies & translate words.

Skills you'll gain

Category: Natural Language Processing
Category: Dimensionality Reduction
Category: Feature Engineering
Category: Machine Learning
Category: Bayesian Statistics
Category: Text Mining
Category: Unstructured Data
Category: Artificial Intelligence
Category: Supervised Learning
Category: Regression Analysis

Natural Language Processing with Probabilistic Models

Course 230 hours4.7 (1,734 ratings)

What you'll learn

  • Use dynamic programming, hidden Markov models, and word embeddings to implement autocorrect, autocomplete & identify part-of-speech tags for words.

Skills you'll gain

Category: Natural Language Processing
Category: Markov Model
Category: Algorithms
Category: Artificial Neural Networks
Category: Text Mining
Category: Machine Learning
Category: Computer Programming
Category: Probability & Statistics
Category: Deep Learning
Category: Unstructured Data
Category: Data Processing
Category: Artificial Intelligence

Natural Language Processing with Sequence Models

Course 321 hours4.5 (1,153 ratings)

What you'll learn

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

Skills you'll gain

Category: Natural Language Processing
Category: Tensorflow
Category: Keras (Neural Network Library)
Category: Artificial Neural Networks
Category: Machine Learning
Category: Deep Learning
Category: Text Mining
Category: PyTorch (Machine Learning Library)

Natural Language Processing with Attention Models

Course 426 hours4.4 (1,044 ratings)

What you'll learn

  • Use encoder-decoder, causal, & self-attention to machine translate complete sentences, summarize text, and answer questions.

Skills you'll gain

Category: Natural Language Processing
Category: Tensorflow
Category: Machine Learning Methods
Category: Data Processing
Category: Deep Learning
Category: Artificial Intelligence
Category: PyTorch (Machine Learning Library)
Category: Text Mining
Category: Keras (Neural Network Library)

Instructors

Eddy Shyu
DeepLearning.AI
14 Courses1,153,373 learners

Offered by

DeepLearning.AI

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