Link to tweet for details on Giveaway: https://twitter.com/bhutanisanyam1/status/1263500914427494400?s=20
\nDiscount code: "PodChai20"
\nVideo Version: https://youtu.be/f5Qv3eSZpug
\nSubscribe here to the newsletter: https://tinyletter.com/sanyambhutani
\nIn this episode, Sanyam Bhutani interviews three great contributors to PyTorch: Eli Stevens, Luca Antiga, and Thomas Viehmann.
\nThe three are also authors of an upcoming book by Manning Publications: Deep learning with Pytorch
\nIn this interview, they talk about the authors' journey into machine learning and the journey with Pytorch towards the efforts into writing the book.
\nThey also discuss the book writing efforts, the authors share what can one expect from the book and what are you expected to have prepared before learning from the book and what can you take away from it.
\nThere is also a lot of great advice around project building, which is, is one of the essence to getting your break into the field.
\nLinks:
\nLink to the book: https://www.manning.com/books/deep-learning-with-pytorch
\nPyTorch: https://pytorch.org
\nFollow:
\nEli Stevens:
\nhttps://www.linkedin.com/in/eli0stevens/
\nLuca Antiga:
\nhttps://twitter.com/lantiga?lang=en
\nhttps://lantiga.github.io
\nThomas Viehmann:
\nhttps://twitter.com/thomasviehmann
\nhttp://thomas.viehmann.net
\nSanyam Bhutani:
\nhttps://twitter.com/bhutanisanyam1
\nBlog: sanyambhutani.com
\nAbout:
\nhttps://sanyambhutani.com/tag/chaitimedatascience/
\nA show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.
\nYou can expect weekly episodes every available as Video, Podcast, and blogposts.
\nIf you'd like to support the podcast: https://www.patreon.com/chaitimedatascience
\nIntro track:
\nFlow by LiQWYD https://soundcloud.com/liqwyd
\nNote: Thanks to Manning Publication for doing the giveaway, note that manning hasn't sponsored the video in anyway, I'm a huge fan of their book and I'm grateful that they're doing a special giveaway + discount for the CTDS.Show audience
\n#MachineLearning #PyTorch #Book