Gavita Regunath

Behind every insight, every model, every dashboard there's a data engineer making it possible. As AI accelerates demand for reliable, real-time data, the role of the data engineer is more critical than ever. Yet the talent pipeline isn't keeping pace, leaving organisations competing for a limited pool of skilled engineers. In this panel, experts from Legal & General, Advancing Analytics, Sky and E.ON Next share how they're navigating this challenge, from building pipelines that power machine learning at scale, to growing talent internally, rethinking hiring strategies, and creating environments where engineers want to stay. Learn how our panellists define what it takes to build and retain world-class engineering capability in a fiercely competitive market. Powered by: Women in Data®

Databricks now offers two paths for building enterprise AI agents: AgentBricks and Mosaic AI. Join Tori and Gavi, 2 AI MVPs as they compare these capabilities, architecture, and ideal use cases. We’ll explore how AgentBricks simplifies agent creation with automated evaluation, synthetic data,...

Machine learning is a forever-evolving space. In the early days, the focus was on implementing the historic algorithms using the computing power that was previously unavailable. Currently, ML has expanded across multiple avenues of interest: Being able to scale models with the ever-increasing quantities of data, the ability to package models up so that they can fit into an MLOps framework, how well tracked and logged the models are, how explainable they are, not to mention techniques to squeeze the best performance out of the models. All these aspects are rarely covered all at once. This pre-con aims to take all these key topics and deliver them over the Databricks platform, one of the leading tools in the industry for data manipulation, machine learning and distributed computing. It utilises a powerful Spark engine under the hood whilst presenting an easy-to-use bespoke notebook for the front end. This session calls upon experience gained over the years by experienced machine learning practitioners to deliver a condensed, concise course to help fast-track any machine learning novice towards mastery. The pre-con will cover building real-world models in Azure, further techniques for robust model building, the latest craze in ML known as feature stores, advanced model tracking and key considerations when scoring models. The pre-con will contain talks, coupled with follow-along labs giving an element of hand-holding with some more tricky tasks thrown in. The sessions will also explore real-world use cases that are rife in the business world.

In today's fast-paced world, businesses need to stay ahead of the curve with innovative technologies. Automated Machine Learning (AutoML) is a powerful tool that enables data teams to quickly build and deploy machine learning models, reducing the time and expertise required to generate a model. This session will provide a comprehensive overview of AutoML on Microsoft Azure, including an introduction to developing ML models using AutoML and exploring options for model deployment. We will compare and contrast the features of both Azure Machine Learning Service and Azure Databricks, helping you decide which platform is best suited to your specific needs. Attendees will learn how to use AutoML to accelerate their ML development process, streamline model creation and deployment, and gain insights into the latest advancements in AutoML technology. This session is perfect for data scientists, developers, and anyone interested in leveraging AutoML to accelerate their ML journey.

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...

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...

Use Databricks to get to grips with the diverse range of machine learning topics. Fast-track your machine learning ability, looking at the latest crazes in machine learning.

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

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. This session aims to provide an introduction to AutoML that will empower developers, analysts, and data scientists to develop machine learning models more quickly.

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...