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
Sequence Models
This course is part of Deep Learning Specialization
Instructors: Andrew Ng
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4.8
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Intermediate level
Recommended experience
Flexible schedule
Approx. 37 hours
Learn at your own pace
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Assessments
4 assignments
Taught in English
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This course is part of the Deep Learning 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 videos3 readings1 assignment2 programming assignments
What's included
5 videos5 readings1 assignment1 programming assignment3 ungraded labs
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4.9 (2,641 ratings)Offered by
Recommended if you're interested in Machine Learning
University of California San Diego
Illinois Tech
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