Sequence Models

Instructor: Andrew Ng , Kian Katanforoosh , Younes Bensouda Mourri

Intermediate Level • 1 week at 10 hours a week • Flexible Schedule

Skills You'll Gain

Tensorflow
Natural language processing
Large Language Modeling
PyTorch (Machine Learning Library)
Deep Learning
Artificial Neural Networks
Artificial Intelligence and Machine Learning (AI/ML)
Applied Machine Learning

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

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,

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.

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.