Recurrent Neural Networks with TF2.0
In this session we will explore Recurrent Neural Networks (RNN) – a type of neural networks specially designed to process sequences – and their applications to time series and text processing (NLP). To make the session even more interesting, all the code will be developed using the latest version of TensorFlow 2.0, using the implementation of the models to discuss the major changes with respect to versions 1.x of the Deep Learning framework, and it will leverage MLFLlow within Azure Databricks as a development platform and model serving.
Principal Data Architect at Plain Concepts & Microsoft AI MVP
Data Engineer at Plain Concepts
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