31 min listen
Building at the intersection of machine learning and software engineering
Building at the intersection of machine learning and software engineering
ratings:
Length:
49 minutes
Released:
May 2, 2024
Format:
Podcast episode
Description
Bringing machine learning models into production is challenging. This is why, as demand for machine learning capabilities in products and services increases, new kinds of teams and new ways of working are emerging to bridge the gap between data science and software engineering. Effective Machine Learning Teams — written by Thoughtworkers David Tan, Ada Leung and Dave Colls — was written to help practitioners get to grips with these challenges and master everything needed to deliver exceptional machine learning-backed products. In this episode of the Technology Podcast, the authors join Scott Shaw and Ken Mugrage to discuss their book. They explain how it addresses current issues in this space, taking in everything from the technical challenges of testing and deployment to the cultural work of building teams that span different disciplines and areas of expertise. Learn more about Effective Machine Learning Teams: https://www.thoughtworks.com/insights/books/effective-machine-learning-teams Read a Q&A with the authors: https://www.thoughtworks.com/insights/blog/machine-learning-and-ai/author-q-and-a-effective-machine-learning-teams
Released:
May 2, 2024
Format:
Podcast episode
Titles in the series (100)
Models of open sourcing software: Open source has become an important model for building interest and trust in a software project. But there’s no one-size-fits-all approach to open source. In this episode our podcasters explore different ways to approach open source and examine... by Thoughtworks Technology Podcast