Aliaksei Mikhailiuk joins the Adventure to discuss the tools he wishes he'd mastered before getting his PhD in Machine Learning. However, the conversation meanders through his background, what qualifications people should have, algorithms, and approaches to machine learning along with the tools discussion.

Michael Berk joins the adventure to discuss how he uses Machine Learning within the context of A/B testing features within applications and how to know when you have a viable test option for your setup.

Pier Paolo Ippolito joins the adventure to discuss some of the paradoxes or counterintuitive generalizations people make about their datasets. Ben, Chuck, and Pier dive into how to look at statistical data and how to identify trends in the data.

The panel jumps in to attempt to break your mental build regarding testing your ML Ops. They advocate for good testing practices around your code and systems and discuss how you can reliable test the various parts of your applications including your Machine Learning models.

Ahmad Mustafa Anis joins the adventure to discuss how he deploys his Machine Learning models using FastAPI. FastAPI is a system for connecting and running Python programs. If your model is built in Python, you can use FastAPI to deploy to Heroku or similar services.

Emeli Dral and Elena Samuylova joins the Adventure to discuss the tools they have built to monitor data quality to determine where data problems occur, what they mean, and how to fix them.

Demetrios Brinkmann joins the adventure to discuss how he build and supports the MLOps Slack community and online meetups. He goes into the community, moderation, running meetups, sponsorships, and much more.

Conor Murphy joins the adventure to explain how he approaches new problems from customers at databricks and how he helps customers see their way past issues with their current solutions to get the outcomes they want.

Antonio Alegria is the head of AI at Outsystems. He leads the effort to find ways to use AI to augment people's experience building software. He joins in to talk about how Outsystems approaches exploring and implementing AI to make the lifecycle of software development easier.

Slater Victoroff joins the Adventure to discuss mutli-modal AI and machine teaching with the panel. He starts out explaining what multi-modal AI is and how it works. The conversation goes deep before veering into Machine Teaching.

Sydney Lai joins the Adventure to discuss how she and her colleagues build AI assisted features for developers and how that they handle scenarios that they can't always plan for.

Sandeep Uttamchandani joins the Adventure to discuss the relationships between Data Science and Machine Learning. He walks through the ways you should set up, manage, and consider the data you use to build and train your Machine Learning systems to get the outcomes that you want.

Alexey Grigorev joins the Adventure to discuss how software engineers can begin making the transition from Software Engineer to Data Scientist in their career.

Ken Youens-Clark joins the adventure to discuss how to write well factored code with tests to help ML be more approachable. He, Ben, and Chuck discuss what it takes to write good code that runs efficiently, is easy to maintain, and still get ML work done.

Mark Ryan is our first returning guest to the Adventure. He has created a video series for Manning showing how to use Machine Learning for Tabular data.