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Course
- Cloud
Sequence Models for Time Series and Natural Language Processing on Google Cloud
In this course, we’ll learn how to make predictions on sequences of data.
What you'll learn
In this course, we’ll learn how to make predictions on sequences of data. We’ll cover common business use cases like- 1.time-series prediction and how to deal with more recent data points getting more relevance 2.translating entire sentences (aka sequences of words) into other languages 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.
Table of contents
- Course Introduction | 1m 53s
- Sequence data and models | 5m 24s
- From sequences to inputs | 2m 42s
- Modeling sequences with linear models | 2m 53s
- Getting started with GCP and Qwiklabs | 3m 48s
- Lab intro:using linear models for sequences | 20s
- Lab: Time Series Prediction with a Linear Model | 10s
- Lab solution:using linear models for sequences | 7m 12s
- Modeling sequences with DNNs | 2m 44s
- Lab intro:using DNNs for sequences | 19s
- Lab: Time Series Prediction with a DNN Model | 10s
- Lab solution:using DNNs for sequences | 2m 18s
- Modeling sequences with CNNs | 3m 35s
- Lab intro:using CNNs for sequences | 19s
- Lab: Time Series Prediction with a CNN Model | 10s
- Lab solution:using CNNs for sequences | 3m 45s
- The variable-length problem | 4m 24s
