Maintaining Backward Compatibility in Software Projects: Strategies from Industry Experts - ML 164

Maintaining Backward Compatibility in Software Projects: Strategies from Industry Experts - ML 164

Today, host Michael Berk and Ben Wilson dive deep into the multifaceted world of software engineering and data science with their insightful guest, Sandy Ryza a lead engineer from Dagster Labs. In this episode, they explore a range of intriguing topics, from the impact of the broken windows theory on code quality to the delicate balance of maintaining backward compatibility in evolving software projects.
Sandy talks about the challenges and learnings in transitioning from data science back to software engineering, including dependency management and designing for diverse use cases. They touch on the importance of clear naming conventions, tooling, and infrastructure enforcement to maintain high code quality. Plus, they discuss the intricate process of selecting and managing Python libraries, the satisfaction of refactoring old code, and the necessity of balancing new feature development with stability.
Michael and Ben will guide us through these essential discussions, emphasizing the significance of user-centric API design and the benefits of open source software. They also get practical advice on navigating API changes and managing dependencies effectively, with real-world examples from Dagster, Spark Time Series, and the libraries Numba and Pydantic.
Join them for an episode packed with valuable insights and strategies for becoming a top-end developer! Don’t forget to follow Sandy on Twitter and check out Dagster.io for more information on his work.

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Why Authenticity Beats Algorithms: The New Rules of Digital Marketing - ML 185

Why Authenticity Beats Algorithms: The New Rules of Digital Marketing - ML 185

In this episode, we dive deep into the evolving landscape of digital marketing and brand storytelling. We explore how the intersection of authenticity, community, and technology is reshaping how brand...

4 Apr 202555min

Integrating Business Needs and Technical Skills in Effective Model Serving Deployments - ML 184

Integrating Business Needs and Technical Skills in Effective Model Serving Deployments - ML 184

Welcome back to another episode of Adventures in Machine Learning, where hosts Michael Berk and Ben Wilson delve into the intricate process of implementing model serving solutions. In this episode, th...

13 Feb 202551min

Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183

Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183

Welcome to another insightful episode of Top End Devs, where we delve into the fascinating world of machine learning and data science. In this episode, host Charles Max Wood is joined by special guest...

24 Jan 202555min

Cows, Camels, and the Human Brain - ML 182

Cows, Camels, and the Human Brain - ML 182

What do cows and camels have to do with the human brain? The latest developments in machine learning, of course! In this episode, Michael and Ben dive into a new white paper from Facebook AI researche...

9 Jan 202542min

A/B Testing with ML ft. Michael Berk - ML 181

A/B Testing with ML ft. Michael Berk - ML 181

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 setu...

2 Jan 202545min

Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180

Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180

In today's episode, we dive into the critical decision-making process of building versus buying technology solutions, especially when it comes to agentic logic-based frameworks. With the industry stil...

26 Dec 202431min

Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy - ML 179

Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy - ML 179

Peter Elger and Eóin Shanaghy join Charles Max Wood to dive into what Artificial Intelligence and Machine Learning related services are available for people to use. Peter and Eóin are experts in AWS a...

19 Dec 202454min

Combating Burnout in Machine Learning: Strategies for Balance and Collaboration - ML 178

Combating Burnout in Machine Learning: Strategies for Balance and Collaboration - ML 178

In this episode, Ben and Michael explore burnout, particularly in machine learning and data science. They highlight that burnout stems from exhaustion, cynicism, and inefficiency and can be caused by ...

12 Dec 20241h 12min

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