Sequence Models for Time Series and Natural Language Processing

Por: Coursera . en: , ,


This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length.

• Predict future values of a time-series
• Classify free form text
• Address time-series and text problems with recurrent neural networks
• Choose between RNNs/LSTMs and simpler models
• Train and reuse word embeddings in text problems

You will get hands-on practice building and optimizing your own text classification and sequence models on a variety of public datasets in the labs we’ll work on together.

Prerequisites: Basic SQL, familiarity with Python and TensorFlow