What courses are included in the sequence models course?
Neural Networks, Deep Learning, Hyper Tuning, Regularization, Optimization, Data Processing, Convolutional NN, Sequence Models are including this Course. Sequence Models by Andrew Ng on Coursera.
What is a sequence model?
A form of sequence models are Recurrent Neural Networks (RNN) which are often used to process speech data (e.g. speech recognition, machine translation), generative models (e.g. generating music) or NLP (e.g. sentiment analysis, named entity recognition (NER), …).
What are the constraints of a sequence model?
The only constraint is that either the input or the output is a sequence. In other words, you may use sequence models to address any type of supervised learning problem which contains a time series in either the input or output layers. In this article, I will discuss 11 key lessons that I learned while taking the course.
How do you augment a sequence model?
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. Join for free and get personalized recommendations, updates and offers.
Sequence Models | Coursera
GitHub – asenarmour/Sequence-models-coursera: …
