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
451,593 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(31,146 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: Artificial Neural Networks
- Category: Natural Language Processing
- Category: Generative AI
- Category: Deep Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Supervised Learning
- Category: Large Language Modeling
- Category: PyTorch (Machine Learning Library)
- Category: Tensorflow
Details to know
Shareable certificate
Add to your LinkedIn profile
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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- Gain a foundational understanding of a subject or tool
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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 (2,823 ratings)Top Instructor
Andrew Ng
DeepLearning.AI
51 Courses9,320,209 learners
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DeepLearning.AI
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4.8
31,146 reviews
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Showing 3 of 31146
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.
JR
5
Reviewed on May 25, 2019
I am so grateful that Andrew and the team provided such good course, I learn so much from this course, I am so excited that see the wake word detection model actually work in the programming exercise
MK
5
Reviewed on Mar 13, 2024
Cant express how thankful I am to Andrew Ng, literally thought me from start to finish when my school didnt touch about it, learn a lot and decided to use my knowledge and apply to real world projects
Frequently asked questions
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When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.