Deep AutoViML For Tensorflow Models and MLOps Workflows


Aug 09, 05:30PM PDT(12:30AM GMT).
  • Free 270 Attendees
Description
Speaker
deep_autoviml is a powerful new deep learning library with a very simple design goal: Make it as easy as possible for novices and experts alike to experiment with and build tensorflow.keras preprocessing pipelines and models in as few lines of code as possible.

deep_autoviml will enable data scientists, ML engineers and data engineers to fast prototype tensorflow models and data pipelines for MLOps workflows using the latest TF 2.4+ and keras preprocessing layers. You can now upload your saved model to any Cloud provider and make predictions out of the box since all the data preprocessing layers are attached to the model itself!

In this webinar, we will discuss the problems that deep_AutoViML can solve, its architecture design and demo how to build powerful TF.Keras models on structured data, NLP and Image data domains.

Ram Seshadri(Google)

Machine Learning Program Manager at Google, Data Scientist with deep experience in financial services and tech/media/telecom. Ram was formerly a Data Scientist at Morgan Stanley and an instructor at General Assembly & New York Institute of Finance.
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