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Sequence Models
  • Level Professional
  • Duration 37 hours
  • Course by DeepLearning.AI
  • Offered by

About

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. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career.

Modules

Recurrent Neural Networks

    • 12 Videos
    • 3 Readings
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12 Videos

  • Why Sequence Models?
  • Notation
  • Recurrent Neural Network Model
  • Backpropagation Through Time
  • Different Types of RNNs
  • Language Model and Sequence Generation
  • Sampling Novel Sequences
  • Vanishing Gradients with RNNs
  • Gated Recurrent Unit (GRU)
  • Long Short Term Memory (LSTM)
  • Bidirectional RNN
  • Deep RNNs

3 Readings

  • [IMPORTANT] Have questions, issues or ideas? Join our Forum!
  • Clarifications about Upcoming Gated Recurrent Unit (GRU) Video
  • Clarifications about Upcoming Long Short Term Memory (LSTM) Video

Lecture Notes (Optional)

    • 1 Readings
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1 Readings

  • Lecture Notes W1

Quiz

    • 1 Assignment
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1 Assignment

  • Recurrent Neural Networks

Programming Assignments

    • 1 Readings
    • 3 Programming
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3 Programming

  • Building your Recurrent Neural Network - Step by Step
  • Dinosaur Island-Character-Level Language Modeling
  • Jazz Improvisation with LSTM

1 Readings

  • (Optional) Downloading your Notebook, Downloading your Workspace and Refreshing your Workspace

Introduction to Word Embeddings

    • 4 Videos
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4 Videos

  • Word Representation
  • Using Word Embeddings
  • Properties of Word Embeddings
  • Embedding Matrix

Learning Word Embeddings: Word2vec & GloVe

    • 4 Videos
    • 1 Readings
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4 Videos

  • Learning Word Embeddings
  • Word2Vec
  • Negative Sampling
  • GloVe Word Vectors

1 Readings

  • Clarifications about Upcoming GloVe Word Vectors Video

Applications Using Word Embeddings

    • 2 Videos
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2 Videos

  • Sentiment Classification
  • Debiasing Word Embeddings

Lecture Notes (Optional)

    • 1 Readings
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1 Readings

  • Lecture Notes W2

Quiz

    • 1 Assignment
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1 Assignment

  • Natural Language Processing & Word Embeddings

Programming Assignments

    • 2 Programming
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2 Programming

  • Operations on Word Vectors - Debiasing
  • Emojify

Various Sequence To Sequence Architectures

    • 8 Videos
    • 1 Readings
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8 Videos

  • Basic Models
  • Picking the Most Likely Sentence
  • Beam Search
  • Refinements to Beam Search
  • Error Analysis in Beam Search
  • Bleu Score (Optional)
  • Attention Model Intuition
  • Attention Model

1 Readings

  • Clarifications about Upcoming Attention Model Video

Speech Recognition - Audio Data

    • 2 Videos
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2 Videos

  • Speech Recognition
  • Trigger Word Detection

Lecture Notes (Optional)

    • 1 Readings
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1 Readings

  • Lecture Notes W3

Quiz

    • 1 Assignment
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1 Assignment

  • Sequence Models & Attention Mechanism

Programming Assignments

    • 1 Readings
    • 2 Programming
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2 Programming

  • Neural Machine Translation
  • Trigger Word Detection

1 Readings

  • Instructions If You Are Unable to Open Your Notebook

Transformers

    • 4 Videos
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4 Videos

  • Transformer Network Intuition
  • Self-Attention
  • Multi-Head Attention
  • Transformer Network

Lecture Notes (Optional)

    • 1 Readings
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1 Readings

  • Lecture Notes W4

Quiz

    • 1 Assignment
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1 Assignment

  • Transformers

End of access to Lab Notebooks

    • 1 Readings
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1 Readings

  • [IMPORTANT] Reminder about end of access to Lab Notebooks

Programming Assignment

    • 1 Programming
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1 Programming

  • Transformers Architecture with TensorFlow

Transformer Applications - Ungraded Labs

    • 3 Lab
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3 Labs

  • Transformer Pre-processing
  • Transformer Network Application: Named-Entity Recognition
  • Transformer Network Application: Question Answering

Conclusion

    • 1 Videos
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1 Videos

  • Conclusion and Thank You!

References & Acknowledgments

    • 3 Readings
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3 Readings

  • References
  • Acknowledgments
  • (Optional) Opportunity to Mentor Other Learners

Auto Summary

Dive into the world of sequence models with this advanced course in the Deep Learning Specialization. Taught by Coursera, you'll explore applications like speech recognition, chatbots, and NLP. Master RNNs, GRUs, LSTMs, and tools like HuggingFace tokenizers over a 2220-minute duration. Ideal for professionals aiming to advance in AI and deep learning, with starter subscription options available.

Andrew Ng
Instructors

Andrew Ng

Kian Katanforoosh
Instructors

Kian Katanforoosh

Younes Bensouda Mourri
Instructors

Younes Bensouda Mourri