Building and Deploying a Model using AutoML in Azure ML


Model selection and tuning hyperparameters can be a tedious task. Setting up multiple runs, hyperparameter sweeps, and algorithms is usually not a Data Scientist’s favorite part of the job. AutoML is a tool in Azure ML that does all of this for you. There are a variety of algorithms, hyperparameters, and evaluation metrics available that are automatically run based on your defined criteria. In this webinar, we will look at how we can use AutoML for training machine learning models. We will also look at the evaluation metrics and see how we can pick the best model from an AutoML run.

Arham Noman

Arham Noman

Data Scientist at Data Science Dojo

Arham Noman is a Data Scientist at Data Science Dojo. He has worked on a variety of projects ranging from building cloud-based machine learning pipelines to indexing and extracting insights from large unstructured datasets. Arham is also an instructor at Data Science Dojo and takes joy in practicing the “Data Science for everyone” philosophy through his sessions.


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