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.

Łukasz Kaiser
Younes Bensouda Mourri

Instructors: Łukasz Kaiser

136,401 already enrolled

Get in-depth knowledge of a subject
4.6

(5,620 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

(5,620 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.

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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: Machine Translation
Category: Locality-Sensitive Hashing
Category: Sentiment Analysis
Category: Word Embeddings
Category: Vector Space Models

Natural Language Processing with Probabilistic Models

Course 230 hours4.7 (1,717 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: N-gram Language Models
Category: Autocorrect
Category: Parts-of-Speech Tagging
Category: Word2vec

Natural Language Processing with Sequence Models

Course 321 hours4.5 (1,143 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: Word Embedding
Category: Siamese Networks
Category: Sentiment with Neural Nets
Category: Natural Language Generation
Category: Named-Entity Recognition

Natural Language Processing with Attention Models

Course 426 hours4.4 (1,026 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: T5+BERT Models
Category: Neural Machine Translation
Category: Question Answering
Category: Attention Models
Category: Text Summarization

Instructors

Łukasz Kaiser
DeepLearning.AI
4 Courses218,168 learners

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DeepLearning.AI

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