• Emre Kiciman & Amit Sharma - Causal Inference & Microsoft's DoWhy Library

  • 2020/08/13
  • 再生時間: 1 時間 6 分
  • ポッドキャスト

Emre Kiciman & Amit Sharma - Causal Inference & Microsoft's DoWhy Library

  • サマリー

  • Emre Kiciman is the Senior Principal Researcher at Microsoft Research Ai in the Information and Data Sciences group, and Amit Sharma is a Senior Researcher at Microsoft Research India. 

    In this episode of the Humans of Ai, we discuss how Emre and Amit started in the field of Science and Technology and then dive into how they got started in Causal Science. We further explore the concepts around Causal Inference, such as Causal Graphs and Confounding Variables. We then discuss Amit & Emre's new software library, “DoWhy – A Library for Causal Inference,” the motivation behind its creation and its significance.

    Towards the end of the episode, we talk about the advantages/disadvantages of Causal Inference and the ethical usage of bringing such sophisticated tools into Machine Learning.

     

    Learning Resources Mentioned in the Podcast:

     

    Causal Inference Course:

    https://causalinference.gitlab.io/

     

    Upcoming Book on Causal Inference by Emre & Amit:

    https://causalinference.gitlab.io/causal-reasoning-book-chapter1/

     

    Intro & Outro music by Simon Calcinai

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あらすじ・解説

Emre Kiciman is the Senior Principal Researcher at Microsoft Research Ai in the Information and Data Sciences group, and Amit Sharma is a Senior Researcher at Microsoft Research India. 

In this episode of the Humans of Ai, we discuss how Emre and Amit started in the field of Science and Technology and then dive into how they got started in Causal Science. We further explore the concepts around Causal Inference, such as Causal Graphs and Confounding Variables. We then discuss Amit & Emre's new software library, “DoWhy – A Library for Causal Inference,” the motivation behind its creation and its significance.

Towards the end of the episode, we talk about the advantages/disadvantages of Causal Inference and the ethical usage of bringing such sophisticated tools into Machine Learning.

 

Learning Resources Mentioned in the Podcast:

 

Causal Inference Course:

https://causalinference.gitlab.io/

 

Upcoming Book on Causal Inference by Emre & Amit:

https://causalinference.gitlab.io/causal-reasoning-book-chapter1/

 

Intro & Outro music by Simon Calcinai

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