Gavita Regunath

AutoML which stands for Automated Machine Learning empowers data teams to quickly build and deploy machine learning models. It aims to reduce the time and expertise required to generate a machine learning model by automating the heavy lifting of preprocessing, feature engineering, model creation, tuning and evaluation. When it comes to machine learning in Microsoft Azure, there are two main options for running your AutoML: (1) Azure Machine Learning Service and (2) Azure Databricks. This session will aim to introduce how to develop ML models using AutoML on both platforms, as well as the features of each and why you would choose one over the other.

In this talk, we will be leveraging Azure computer vision. The Azure Computer Vision is part of Azure Cognitive Services that provides pre-built, advanced algorithms that process and analyse images. If you want to get started with computer vision but do not know where to start, then this talk will give you a good starting point to jumpstart your computer vision journey. You will leave this talk with an understanding of how to build and deploy your own computer vision models using Azure computer vision.

Ben and Rob have found some wonderful folk to actually do the important parts of the community keynote. on the theme of How to be a nonpassive member of the data community

Come and meet the group working hard to make SQLBits as diverse and inclusive as it can be

Understand how to get started with any machine learning project using Databricks AutoML

In this session, we will cut through the marketing buzzwords to share experiences, tips, and tricks on how to be successful with Data Science and Analytics in the real world. Tune in to hear the team share real-world experience and get takeaways from industry insiders on real projects with impact. We will also discuss the ethics and fairness of Data Science and Analytics projects and how we can be more inclusive from a technology, people, and process standpoint.