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Building at the intersection of machine learning and software engineering
Manage episode 415888000 series 2602635
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 created 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 the field, 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
136 episod
Manage episode 415888000 series 2602635
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 created 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 the field, 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
136 episod
Alla avsnitt
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1 Exploring the intersections of software architecture 43:32

1 Who should make software architecture decisions? 35:00

1 Generative AI's uncanny valley: Problem or opportunity? 28:51

1 Using generative AI for legacy modernization 33:19

1 Data contracts: What are they and why do they matter? 37:38

1 In conversation with Thomas Squeo, Thoughtworks CTO for the Americas 33:09

1 Themes from Technology Radar Vol.31 39:39

1 Build Your Own Radar: Using the Technology Radar as a governance tool 37:11

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