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Thoughtworks에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Thoughtworks 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Building at the intersection of machine learning and software engineering

48:30
 
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Manage episode 415899533 series 2434934
Thoughtworks에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Thoughtworks 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

  continue reading

195 에피소드

Artwork
icon공유
 
Manage episode 415899533 series 2434934
Thoughtworks에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Thoughtworks 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

  continue reading

195 에피소드

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