Sequence Models

This course will teach one how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others.

Students are able to:

  • Understand how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs.
  • Apply sequence models to natural language problems, including text synthesis.
  • Apply sequence models to audio applications, including speech recognition and music synthesis.

This is the fifth and final course of the Deep Learning Specialization. It involved a deep learning project with cutting-edge, industry-relevant content.

Aditya Jyoti Paul
Aditya Jyoti Paul
Computer Vision and Image Encryption Researcher

My work makes machines smarter, secure and more accessible. I’m passionate about research, teaching and blogging. Outside academia, I love travel, music, reading and meeting new people!