camara94/tensorflow-sequences-time-series-and-prediction

In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data

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This project helps data scientists, machine learning engineers, and researchers build and apply time series prediction models using TensorFlow. It guides users through preparing time series data, building models with RNNs and 1D ConvNets, and evaluating predictions. The input is structured time series data, and the output is a predictive model capable of forecasting future values or identifying patterns.

No commits in the last 6 months.

Use this if you are a data scientist or machine learning engineer looking to build, train, and deploy advanced time series forecasting models for diverse applications like weather, stock prices, or anomaly detection.

Not ideal if you are looking for a no-code solution or a simple, off-the-shelf time series analysis tool without needing to delve into model architecture and training.

time-series-forecasting predictive-modeling anomaly-detection financial-forecasting environmental-modeling
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

12

Forks

5

Language

Jupyter Notebook

License

MIT

Last pushed

May 05, 2022

Commits (30d)

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