Should Data Scientists Care About Microsoft Fabric?

Microsoft Fabric has emerged as the new one-stop-shop for Azure data platforms, but what does that mean for us Data Scientists? Is there anything here for the Machine Learning practitioner?

In this talk we will explore the brand new features of Fabric's data science stack including model tracking with MLFlow, model registries and SynapseML. We will explore how to get started with your very first model in Fabric and how the platform compares to it's competitors.

Real Time Scoring using Azure Functions

Introduction to Building Scalable Machine Learning Models

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.

Ask the Expert - Group B (Fri: 9:00 to 9:50)

Got a problem? Don't know who to call? Bring it to SQLBits and get it solved by our panel of experts!

More information can be found here:
https://sqlbits.com/news/ask-the-experts-at-the-experts-lounge/

5. Data Science and Analytics: Alexander Billington
7. Programming and Development:
8. Data Management and Governance: Ben DeBow
9. User Experience and Design: Kerry Kolosko

Ask the Expert - Group B (Wed: 13:50 to 15:40)

'Got a problem? Don't know who to call? Bring it to SQLBits and get it solved by our panel of experts!

More information can be found here:
https://sqlbits.com/news/ask-the-experts-at-the-experts-lounge/

5. Data Science and Analytics:
6. Microsoft Tools and Technologies:
7. Programming and Development:
8. Data Management and Governance:
9. User Experience and Design:

Your experts on these subjects are:
13:50 to 14:40
5. Alexander Billington
7. Vuong Nguyen, Ed Freeman
8 Liping Huang
9 Carole McNally

14:50 to 14:40
5
7
8
9 Robert French

First Class MLOps with Databricks

Arguably the largest challenge in ML today is effectively deploying reliable and efficient models into production, with experts quoting that as many as 80% of model created never make it to production. MLOps streamlines the process of taking machine learning models to production, and then maintaining and monitoring them. With new MLOps micro-venders popping up every day, is there a tool that does everything?

In this session, we will consider Databricks as an end-to-end MLOps tool, exploring collaborative workspaces, feature stores, model registries and model serving, touching upon other critical MLOps practices such as model fairness, explainability and monitoring.

Including practical demos of Databricks Feature Store, MLFlow, Drift Monitoring and real-time Model Serving, this session is suitable for Data Scientists and Machine Learning Engineers of all levels.