Adventures in Machine Learning


Ben Wilson

Michael Berk

Charles Max Wood

Gant Laborde

Daniel Svoboda

Jason Mayes

Beril Sirmacek

Miguel Morales

Francois Bertrand



May 25, 2023

The Innovation Cycle of AI - ML 116

Today we speak with ex-Googler, Praveen Paritosh. He has over 20 years of experience as a research scientist and has worked on some of AI's most impactful projects. Expect to learn about scientific innovation, the importance of data, and the next wave of AI (spoiler, it's not LLMs).

May 11, 2023

All Things Machine Learning - ML 115

Host from the Ruby Rogues podcast, Dave Kimura joins Ben and Michael for this week's crossover episode. They discuss applying machine learning and deep learning, and how artificial intelligence changes the future.

May 05, 2023

How to Transition from Academics to Industry - ML 114

Today we speak with Noah Silbert, a former data scientist at Netflix and current data scientist at Tubi. Expect to learn about company size can impact your role and day-to-day work as a data scientist. We also cover Noah's experience moving from being a professor to handling the scale and complexity of the tech industry.

Michael Berk
Apr 27, 2023

How to Make your Projects Succeed - ML 113

In today's episode, we walk through a project that Michael is currently working on. Expect to learn about scoping a project, getting feedback, and ensuring value.

Apr 13, 2023

How to Think Like a Principal Architect - ML 112

Today, we do a deep dive into Ben's background. We cover his career trajectory and, more importantly, how nature and nurture have impacted the way he thinks.

Apr 07, 2023

How to Transition from Software Engineer to ML Engineer - ML 111

Today we speak with a software engineer who is interested in becoming an ML engineer. Expect to learn about ML roles that are most attainable based on a strong software engineering skill set. We also cover some tangible strategies you can leverage to make the transition.

Mar 30, 2023

Machine Learning for Meeting Notes - ML 110

Today we look at an applied use case for ML: developing intelligent meeting notes. Expect to learn about LLMs, AI assistants, and how to develop an AI startup.

Mar 26, 2023

Model Serving at Databricks - ML 109

Today we deep dive into the mind of two brilliant Databricks software engineers. Their primary project was building the model serving feature, but expect to learn about ML side projects, traits of successful software engineers, and much more!

Mar 17, 2023

Where ML and DevOps Meet - ML 108

Hosts of the Adventures in DevOps podcast, Jillian Rowe and Jonathan Hall, join Ben and Michael on this week's episode crossover. They talk about the intersection of ML and DevOps. They dive into the concepts and differences between ML and DevOps. Additionally, they talk about how ML ideas may be applied to DevOps principles and vice versa.

Mar 10, 2023

How Does ChatGPT Work? - ML 107

ChatGPT is the most robust free chatbot. It can answer questions, write code, and summarize text. Today we will talk about the creation of ChatGPT, its implications for society, and how the model actually works.

Mar 03, 2023

Machine Learning for Movie Scripts - ML 106

Today we look at an applied use case for ML: parsing movie scripts. Expect to learn about bringing ML to new industries, the future of Large Language Models (LLM), and automation in the movie industry.

Feb 23, 2023

ChatGPT and the Divine - ML 105

"Any sufficiently advanced technology is indistinguishable from magic." Today, Michael and Ben talk about the broad implications of ChatGPT and similar algorithms. Expect to learn about...

Feb 16, 2023

Deep Learning for Tabular and Time Series Data - ML 104

Today we speak with a staff data scientist at Walmart who specializes in forecasting. He has built an open-source tool that allows you to leverage tabular data in PyTorch. He also has written a book on time series forecasting with deep learning.

Feb 09, 2023

Notebooks vs. IDEs With Fabian Jakobs - ML 103

How do you develop ML code? Do you use notebooks or do you use IDEs? In this episode, we get some practical advice from both Ben and our guest on leveraging software principles to write better code in both an IDE and notebook environment. We'll also learn about a cool new Databricks feature that will help you run ML code from an IDE.

Feb 03, 2023

How To Think About Optimization - ML 102

In this week's episode, we meet with Micheal McCourt, the head of engineering at SigOpt. He is an industry expert on optimization algorithms, so expect to learn about constraint-active search, SigOpt's new open-source optimizer, and how to run an engineering team.

Jan 27, 2023

Protecting Your ML From Phishing And Hackers - ML 101

Have you ever wondered how to secure a cloud deployment? Well, today we talk to the president at a cloud security company about personal security, detecting malicious actors, startup trends, and much more!

Jan 19, 2023

The Disruptive Power of Artificial Intelligence - ML 100

Have you ever wondered about the most promising industries in Machine Learning? Today we will learn from Avi Goldfarb, the chair of AI at the University of Toronto, about... -The most promising AI industries -Potential problems with powerful AI -The economics behind innovation

Jan 05, 2023

A History Of ML And How Low Code Tooling Accelerates Solution Development - ML 099

In this episode, Ben talks with Rosaria Silipo, a Software Engineer and Developer Relations advocate at Knime. They discuss the benefits of low-code ML, delve into the history of ML development work as it has changed over the past few decades, and discuss a few stories about the importance of pursuing simplicity in implementations.

Ben Wilson

Rosaria Silipo
Dec 22, 2022

Moving from Dev Notebooks to Production Code - ML 098

In this week's episode we meet with Mike Arov, committer to the MLOps tool framework lineapy. From the benefits of notebooks as development tooling for Data Science work to the complex refactoring needed to convert them to production-capable code bases, our conversation dives deep into the generally under-represented bridge tooling of code base conversions.

Ben Wilson

Mike Arov
Dec 15, 2022

How to Edit and Contribute to Existing Code Base - ML 097

Let's be honest. We've all copy and pasted code from the internet. There are many great code sources and in this episode we discuss how to leverage existing code. We'll explain how to understand a code base and some best practices for contribution.

Dec 01, 2022

MLflow 2.0 And How Large-Scale Projects Are Managed In The Open Source - ML 096

Corey Zumar talks about the new release of MLflow, 2.0, and what the new major features that are included in the release. Bilal and Corey then discuss managing feature implementation priorities, and selling large-scale project ideas to internal customers, end-users, executives, and the dev team. The discussion also centers around generalizing feature requests to implementations that will work for the masses and how to effectively do prototype releases for incremental agile development for complex projects.

Nov 24, 2022

How To Recession Proof Your Job - BONUS

Are you looking at all the layoffs and uncertainty going on and wondering if your company is the next to cut back?    Or, maybe you're a freelancer or entrepreneur who is trying to figure out how to deliver more value to gain or retain customers?    Mani Vaya joins Charles Max Wood to discuss the one thing that both of them use to more than double their productivity on a daily basis.    Mani has read 1,000's of productivity books over the last several years and has formulated a methodology for getting more done, but found that he lacked the discipline to follow through on his plans.    The he found the one thing that kept him on track and made him so productive that he is now getting all of his work done and was able to live the life he wants.    Chuck also weighs in on how Mani's technique has worked for him and allows him to spend more time with his wife and kids, run a podcast network, and a nearly full time contract.    Join the episode to learn how Chuck and Mani get into a regular flow state with their work and consistently deliver at work. 

Charles Max Wood

Mani Vaya
Nov 24, 2022

Should you Context Switch when Writing Code? - ML 095

Do you multitask? If so, you'll want to check out this episode. We'll cover...

Nov 17, 2022

Important Questions To Ask When Scoping ML Projects - ML 094

Have you ever wondered how to prioritize your ML projects? Today we will talk about...

Nov 10, 2022

How To Do Research Spikes - ML 093

Have you ever wondered how to efficiently learn topics? In this episode, we discuss how to conduct a research spike within an ML team setting.