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Nội dung được cung cấp bởi Alexandre Andorra. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Alexandre Andorra hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.
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#58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng Lao

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Manage episode 323371695 series 2635823
Nội dung được cung cấp bởi Alexandre Andorra. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Alexandre Andorra hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

You know when you have friends who wrote a book and pressure you to come on your podcast? That’s super annoying, right?

Well that’s not what happened with Ravin Kumar, Osvaldo Martin and Junpeng Lao — I was the one who suggested doing a special episode about their new book, Bayesian Modeling and Computation in Python. And since they cannot say no to my soothing French accent, well, they didn’t say no…

All of them were on the podcast already, so I’ll refer you to their solo episode for background on their background — aka backgroundception.

Junpeng is a Data Scientist at Google, living in Zurich, Switzerland. Previously, he was a post-doc in Psychology and Cognitive Neuroscience. His current obsessions are time series and state space models.

Osvaldo is a Researcher at CONICET in Argentina and the Department of Computer Science from Aalto University in Finland. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling.

Ravin is a data scientist at Google, living in Los Angeles. Previously he worked at Sweetgreen and SpaceX. He became interested in Bayesian statistics when trying to quantify uncertainty in operations. He is especially interested in decision science in business settings.

You’ll make your own opinion, but I like their book because uses a hands-on approach, focusing on the practice of applied statistics. And you get to see how to use diverse libraries, like PyMC, Tensorflow Probability, ArviZ, Bambi, and so on. You’ll see what I’m talking about in this episode.

To top it off, the book is fully available online at bayesiancomputationbook.com. If you want a physical copy (because you love those guys and wanna support them), go to CRC website and enter the code ASA18 at checkout for a 30% discount.

Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !

Thank you to my Patrons for making this episode possible!

Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.

Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

Links from the show:


  continue reading

121 tập

Artwork
iconChia sẻ
 
Manage episode 323371695 series 2635823
Nội dung được cung cấp bởi Alexandre Andorra. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Alexandre Andorra hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

You know when you have friends who wrote a book and pressure you to come on your podcast? That’s super annoying, right?

Well that’s not what happened with Ravin Kumar, Osvaldo Martin and Junpeng Lao — I was the one who suggested doing a special episode about their new book, Bayesian Modeling and Computation in Python. And since they cannot say no to my soothing French accent, well, they didn’t say no…

All of them were on the podcast already, so I’ll refer you to their solo episode for background on their background — aka backgroundception.

Junpeng is a Data Scientist at Google, living in Zurich, Switzerland. Previously, he was a post-doc in Psychology and Cognitive Neuroscience. His current obsessions are time series and state space models.

Osvaldo is a Researcher at CONICET in Argentina and the Department of Computer Science from Aalto University in Finland. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling.

Ravin is a data scientist at Google, living in Los Angeles. Previously he worked at Sweetgreen and SpaceX. He became interested in Bayesian statistics when trying to quantify uncertainty in operations. He is especially interested in decision science in business settings.

You’ll make your own opinion, but I like their book because uses a hands-on approach, focusing on the practice of applied statistics. And you get to see how to use diverse libraries, like PyMC, Tensorflow Probability, ArviZ, Bambi, and so on. You’ll see what I’m talking about in this episode.

To top it off, the book is fully available online at bayesiancomputationbook.com. If you want a physical copy (because you love those guys and wanna support them), go to CRC website and enter the code ASA18 at checkout for a 30% discount.

Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !

Thank you to my Patrons for making this episode possible!

Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland and Aubrey Clayton.

Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

Links from the show:


  continue reading

121 tập

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