Sequences, Time Series and Prediction
With an emphasis on time series prediction using RNNs and ConvNets, this course educates software developers on how to create scalable AI models using TensorFlow.
Description for Sequences, Time Series and Prediction
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TensorFlow Best Practices: Instructs on fundamental methodologies for utilizing TensorFlow, an open-source machine learning framework, to develop scalable models.
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Time Series Modeling: Concentrates on constructing time series models, encompassing data preparation methodologies and employing RNNs and 1D ConvNets for forecasting.
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Practical Application: Utilizes acquired skills on real-world data, exemplified by the construction of a sunspot prediction model.
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Fundamental Knowledge: Expands upon concepts from Andrew Ng's Machine Learning course and the Deep Learning Specialization, offering an enhanced comprehension of neural networks and model execution using TensorFlow.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by DeepLearning.AI
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Duration:21 hours (approximately)
Schedule: Flexible
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