Sequence Models for Time Series and Natural Language Processing

Google Cloud

machine-learning   |   Intermediate   |   12 Hours

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

What skills will you gain?

Time Series

natural language

Tensorflow

Word2vec

modeling

Long Short-Term Memory

Natural Language Processing

language

Word Embedding

Document Classification