In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more.
Sequence Models
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Sequence Models
This course is part of Deep Learning Specialization
Instructors: Andrew Ng +2 more
Top Instructor
446,851 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(31,086 reviews)
Intermediate level
Recommended experience
Flexible schedule
4 weeks at 10 hours a week
Learn at your own pace
94%
Most learners liked this course
Skills you'll gain
- Category: Deep Learning
- Category: Natural Language Processing
- Category: PyTorch (Machine Learning Library)
- Category: Artificial Neural Networks
- Category: Supervised Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Large Language Modeling
- Category: Tensorflow
- Category: Generative AI
Details to know
Shareable certificate
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Assessments
4 assignments
Taught in English
Build your subject-matter expertise
This course is part of the Deep Learning Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Discover recurrent neural networks, a type of model that performs extremely well on temporal data, and several of its variants, including LSTMs, GRUs and Bidirectional RNNs,
What's included
12 videos5 readings1 assignment3 programming assignments
Natural language processing with deep learning is a powerful combination. Using word vector representations and embedding layers, train recurrent neural networks with outstanding performance across a wide variety of applications, including sentiment analysis, named entity recognition and neural machine translation.
What's included
10 videos2 readings1 assignment2 programming assignments
Augment your sequence models using an attention mechanism, an algorithm that helps your model decide where to focus its attention given a sequence of inputs. Then, explore speech recognition and how to deal with audio data.
What's included
10 videos2 readings1 assignment2 programming assignments
What's included
5 videos5 readings1 assignment1 programming assignment3 ungraded labs
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Instructors
Instructor ratings
4.9 (2,805 ratings)Top Instructor
Andrew Ng
DeepLearning.AI
51 Courses9,118,638 learners
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DeepLearning.AI
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4.8
31,086 reviews
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Showing 3 of 31086
JS
5
Reviewed on Jul 12, 2020
brilliant course, great quality instruction from Andrew Ng. The only faults are that some of the labs have not been supervised properly being a but buggy and a couple of later lectures were very dry.
SN
5
Reviewed on Mar 30, 2020
It's an exciting course to learn about sequence models. The assignment illustrate the concept via step by step to understand how to implement how to implement the models and process the input data.
MI
5
Reviewed on Oct 15, 2019
This is one of the most comprehensive yet enjoyable courses in the whole specialization! There are several assignments of practical applications. Thanks for the time and effort put into this course.
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