Sequence Models

Intermediate Level
1 week at 10 hours a week
Flexible Schedule

Andrew Ng , Kian Katanforoosh , Younes Bensouda Mourri

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

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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,

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.