DeepLearning.AI
Natural Language Processing in TensorFlow
DeepLearning.AI

Natural Language Processing in TensorFlow

This course is part of DeepLearning.AI TensorFlow Developer Professional Certificate

Taught in English

Some content may not be translated

Laurence Moroney

Instructor: Laurence Moroney

141,062 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.6

(6,435 reviews)

|

94%

Intermediate level

Recommended experience

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

What you'll learn

  • Build natural language processing systems using TensorFlow

  • Process text, including tokenization and representing sentences as vectors

  • Apply RNNs, GRUs, and LSTMs in TensorFlow

  • Train LSTMs on existing text to create original poetry and more

Details to know

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Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.6

(6,435 reviews)

|

94%

Intermediate level

Recommended experience

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

See how employees at top companies are mastering in-demand skills

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This course is part of the DeepLearning.AI TensorFlow Developer Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

The first step in understanding sentiment in text, and in particular when training a neural network to do so is the tokenization of that text. This is the process of converting the text into numeric values, with a number representing a word or a character. This week you'll learn about the Tokenizer and pad_sequences APIs in TensorFlow and how they can be used to prepare and encode text and sentences to get them ready for training neural networks!

What's included

13 videos9 readings1 quiz1 programming assignment

Last week you saw how to use the Tokenizer to prepare your text to be used by a neural network by converting words into numeric tokens, and sequencing sentences from these tokens. This week you'll learn about Embeddings, where these tokens are mapped as vectors in a high dimension space. With Embeddings and labelled examples, these vectors can then be tuned so that words with similar meaning will have a similar direction in the vector space. This will begin the process of training a neural network to understand sentiment in text -- and you'll begin by looking at movie reviews, training a neural network on texts that are labelled 'positive' or 'negative' and determining which words in a sentence drive those meanings.

What's included

13 videos8 readings1 quiz1 programming assignment

In the last couple of weeks you looked first at Tokenizing words to get numeric values from them, and then using Embeddings to group words of similar meaning depending on how they were labelled. This gave you a good, but rough, sentiment analysis -- words such as 'fun' and 'entertaining' might show up in a positive movie review, and 'boring' and 'dull' might show up in a negative one. But sentiment can also be determined by the sequence in which words appear. For example, you could have 'not fun', which of course is the opposite of 'fun'. This week you'll start digging into a variety of model formats that are used in training models to understand context in sequence!

What's included

10 videos8 readings1 quiz1 programming assignment

Taking everything that you've learned in training a neural network based on NLP, we thought it might be a bit of fun to turn the tables away from classification and use your knowledge for prediction. Given a body of words, you could conceivably predict the word most likely to follow a given word or phrase, and once you've done that, to do it again, and again. With that in mind, this week you'll build a poetry generator. It's trained with the lyrics from traditional Irish songs, and can be used to produce beautiful-sounding verse of it's own!

What's included

14 videos8 readings1 quiz1 programming assignment

Instructor

Instructor ratings
4.8 (844 ratings)
Laurence Moroney
DeepLearning.AI
15 Courses495,705 learners

Offered by

DeepLearning.AI

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