Chai Time Data Science

This episode reviews Lesson 8 from fast.ai Part 1, 2019 and the Things Jeremy says to do About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode reviews Lesson 7 from fast.ai Part 1, 2019 and the Things Jeremy says to do About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode reviews Lesson 5 from fast.ai Part 1, 2019 and the Things Jeremy says to do About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode reviews Lesson 4 from fast.ai Part 1, 2019 and the Things Jeremy says to do About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode reviews lesson 2 from fast.ai Part 1, 2019 and the Things Jeremy says to do About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode reviews Lesson 3 from fast.ai Part 1, 2019 and the Things Jeremy says to do About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode is an introduction to the Mini-Chai Time Data Science series, about fast.ai summaries from Part 1, 2019 and a collection of things Jeremy Howard says to do. About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode summarises Lesson 1: Image Classification from fast.ai Part-1 along with the things Jeremy says to do. About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

This episode reviews Lesson 6 from fast.ai Part 1, 2019 and the Things Jeremy says to do About: The motivation behind the 3-4 min video/audio summaries is to allow our fellow fast.ai family members to review the lectures from Part 1, 2019 and "Things Jeremy Says to do" in a 3 min format. Jeremy Howard, mentions many pearls of wisdom that Many Thanks to Robert Bracco, Author of "Things Jeremy Howard says to do" are now also available in this format. Reminder Note: This series is not a replacement in any format for the fast.ai lectures. It's supposed to act as supplementary material for the course. Links: Take the course here: https://course.fast.ai Things Jeremy Says to do thread: https://forums.fast.ai/t/things-jeremy-says-to-do/36682 Follow: fast.ai: http://twitter.com/fastdotai Jeremy Howard: http://twitter.com/jeremyphoward Robbert Bracco: https://twitter.com/MadeUpMasters Sanyam Bhutani: http://twitter.com/bhutanisanyam1

YT Channel: https://www.youtube.com/@ChaiTimeDataScience Learn more about H2O's Hydrogen Torch app here: https://h2o.ai/platform/ai-cloud/make/hydrogen-torch/ In this "episode", Sanyam Bhutani will host the the world's top kagglers and best data scientists to learn and debate the best practises for training ml models.   We will learn from their experience of having won multiple competitions and built many incredible products at H2O: what are the best practises for taming your ml model    Panelists: Dmitry Gordeev:  https://www.kaggle.com/dott1718  https://twitter.com/dott1718 https://www.linkedin.com/in/dmitry-gordeev-50116023/?originalSubdomain=at Gabor Fodor:  https://www.kaggle.com/gaborfodor  https://www.linkedin.com/in/gábor-fodor-6a081548/?originalSubdomain=hu Pascal Pfeiffer:  https://www.kaggle.com/ilu000 https://www.linkedin.com/in/pascal-pfeiffer/ Philipp Singer:  https://www.kaggle.com/philippsinger https://twitter.com/ph_singer https://www.linkedin.com/in/philippsinger/ Yauhen Babakhin: https://www.kaggle.com/ybabakhin https://www.linkedin.com/in/yauhenbabakhin/ Sanyam Bhutani: https://www.kaggle.com/init27 https://twitter.com/bhutanisanyam1 https://www.linkedin.com/in/sanyambhutani/ A show for interviews with Practitioners, Kagglers & Researchers hosted by Sanyam.

Channel: http://youtube.com/c/ChaiTimeDataScience/ Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this Episode, Sanyam Bhutani interviews Amed Coulibaly about his journey and reflection on reaching Kaggle Competitions Grandmaster. They also understand his team's 3rd place solution to recently ended Feedback competition Links: Solution: https://www.kaggle.com/competitions/feedback-prize-english-language-learning/discussion/369609 Follow: Amed Coulibaly: Twitter: https://twitter.com/Amedprof Linkedin: https://www.linkedin.com/in/amed-coulibaly-94150610a/ Kaggle: https://www.kaggle.com/amedprof Sanyam Bhutani: Twitter: https://twitter.com/bhutanisanyam1 LinkedIn: https://www.linkedin.com/in/sanyambhutani/ Kaggle: https://www.kaggle.com/init27 Blog: sanyambhutani.com A show for Interviews with Practitioners, Kagglers & Researchers, and all things Data Science hosted by Sanyam Bhutani.

The show becomes "Coffee Time Data Science" for a one-time special episode! The genesis for this interview was this twitter thread: https://twitter.com/jeremyphoward/status/1503920390447730690 Video version: https://www.youtube.com/watch?v=g_6nQBsE4pU Links from the show: fastai Course: https://course.fast.ai How not to do fastai: https://medium.com/@init_27/how-not-to-do-fast-ai-or-any-ml-mooc-3d34a7e0ab8c Meta Learning Book: https://radekosmulski.gumroad.com/l/learn_deep_learning Rachel’s advice on Blogging: https://medium.com/@racheltho/why-you-yes-you-should-blog-7d2544ac1045 In the frame: Jeremy Howard: https://twitter.com/jeremyphoward Sanyam Bhutani: https://twitter.com/bhutanisanyam1 OUTLINE: 0:00 - Intro 2:40 - Reaching Kaggle Grandmaster Tier 4:46 - Current Work 6:30 - University Education 12:00 - Signing up for fastai 15:49 - Failures with fastai 18:29 - Tenacity 23:40 - Content Creation 33:10 - Sharing your work 36:09 - Educational Content 41:49 - Failing Google AI Residency 46:34 - Starting the podcast 48:19 - Question to Jeremy 52:40 - Thank you

Video Version: https://youtu.be/qObfeWYbrPM In this episode, Sanyam Bhutani interviews the hosts from AI Today Podcast: Kathleen Walch, Ronald Schmelzer They talk about their journey into AI, creating AI Content, and the AI Today Podcast. Links: AI Today Podcast: https://www.cognilytica.com/aitoday/ Cognalytica: https://www.cognilytica.com Follow: Kathleen Walch: Twitter: https://twitter.com/kath0134 Linkedin: https://www.linkedin.com/in/kathleen-walch-50185112/ Ronald Schmelzer: Twitter: https://twitter.com/rschmelzer Linkedin: https://www.linkedin.com/in/rschmelzer/ Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.

Video Version: https://youtu.be/W3aWEXqIkWk Blog Overview: http://sanyambhutani.com/interview-with-the-nvidia-acm-recsys-2021-winning-team Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this Episode, Sanyam Bhutani interviews a panel from the ACM RecSys Winning competition team at NVIDIA. They explain why are RecSys systems such a hard problem, how can GPUs accelerate these, how do we productize such solutions. The team also does a ground basic to a complete overview of their solution. They understand the team's approaches to the problem, how did they arrive at the solution, and the tricks that they discovered and very generously shared in this interview Links: Interview with Even Oldridge: https://youtu.be/-WzXIV8P_Jk Interview with Chris Deotte: https://youtu.be/QGCvycOXs2M Open Source Solution: https://github.com/NVIDIA-Merlin/competitions/tree/main/RecSys2021_Challenge Paper Link: https://github.com/NVIDIA-Merlin/competitions/blob/main/RecSys2021_Challenge/GPU-Accelerated-Boosted-Trees-and-Deep-Neural-Networks-for-Better-Recommender-Systems.pdf Follow: Benedikt Schifferer: Linkedin: https://www.linkedin.com/in/benedikt-schifferer/ Bo Liu: Twitter: https://twitter.com/boliu0 Kaggle: https://www.kaggle.com/boliu0 Chris Deotte: Twitter: https://twitter.com/ChrisDeotte Kaggle: https://www.kaggle.com/cdeotte Even Oldridge Twitter: https://twitter.com/even_oldridge Linkedin: https://www.linkedin.com/in/even-oldridge/ Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers, and all things Data Science hosted by Sanyam Bhutani. 

Personal Note: This was a huge honor for me to meet Harrison and have him on the podcast! In this episode, Sanyam Bhutani interviews THE SentDex about his journey as an entrepreneur, YouTube content creator, Educator and Author. They talk about his journey on and off the platform and the R&D that happens behind the scenes for the incredible videos that we get to see. They also discuss how the NVIDIA DGX A-100 box has been helping Harrison for the few months of usage. Thanks to our friends at NVIDIA for helping make this conversation happen! Link: NNFS.io: https://nnfs.io DGX-A100: https://www.nvidia.com/en-in/data-center/dgx-a100/ Interview with Charlie Boyle: https://www.youtube.com/watch?v=SiUnKGD90uI Follow: Harrison Kinsley: YouTube: https://www.youtube.com/user/sentdex Twitter: https://twitter.com/Sentdex Website: https://hkinsley.com Linkedin: https://www.linkedin.com/in/hkinsley/ Instagram : https://www.instagram.com/sentdex/ Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani. #Python #machinelearning #SentDex

Personal Note: I'm so happy to release a new interview after a really long break! Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews Clair Sullivan, Graph Data Science Advocate at Neo4j They talk about Clair's journey from taking up the challenge and becoming an engineer to later transitioning from academia back into the industry Links:  Neo4j: https://neo4j.com NODES 2021: https://neo4j.com/event/nodes-2021/ Follow: Clair Sullivan: https://twitter.com/CJLovesData1 https://www.linkedin.com/in/dr-clair-sullivan-09914342/ Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.

Personal Note: Season 1 Finale had to be my interview with Emil. Huge thanks everyone for being a part of this journey! Video Version: https://youtu.be/ENbKecYgITA Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews Emil Wallner, Artist in Residence at Google. They talk about Emil's journey from being a kind of a village in Africa to travelling and transitioning into AI. They discuss Emil's tweet storms, his self-taught journey and beyond Link: Meta thread to all of Emil's tweetstorms: https://twitter.com/bhutanisanyam1/status/1278036597523406849?s=20 Follow: Emil Wallner: https://twitter.com/EmilWallner https://github.com/emilwallner Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani. You can expect weekly episodes every available as Video, Podcast, and blogposts. Intro track: Flow by LiQWYD https://soundcloud.com/liqwyd

Personal Note: This was one my favourite Kaggle related interviews. Personally, I found Andrada's journey to be very relatable. Video Version: https://youtu.be/nshTx_EfRKU Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews Andrada Olteanu about her journey to transitioning into Data Science and Learning on Kaggle. They discuss the struggles of learning something new and how to approach Kaggle. Follow: Andrada Olteanu: https://twitter.com/andradaolteanuu https://www.linkedin.com/in/andrada-olteanu-3806a2132/ https://www.kaggle.com/andradaolteanu Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani. You can expect weekly episodes every available as Video, Podcast, and blogposts. Intro track: Flow by LiQWYD https://soundcloud.com/liqwyd

Video Version: https://youtu.be/xDhVLLc4pUk Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews Laura Leal Taixe. They talk about Laura's journey into Academia and her research at the Dynamic Vision & Learning Group. Follow: Laura Leal Taixé: https://twitter.com/lealtaixe https://www.youtube.com/channel/UCQVCsX1CcZQr0oUMZg6szIQ https://dvl.in.tum.de/team/lealtaixe/ Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani. You can expect weekly episodes every available as Video, Podcast, and blogposts. Intro track: Flow by LiQWYD https://soundcloud.com/liqwyd

Video Version: https://youtu.be/xbcGj_mtTB0 Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews the creator of PyTorch Lightning: William Falcon They talk about William's journey from being in the military to the financial world, learning how to code and eventually transitioning into Data Science. They discuss the PyTorch lightning story and William's research, Grid.ai Links: Grid.ai: https://www.grid.ai PyTorch Lightning: https://www.pytorchlightning.ai Blog: https://www.williamfalcon.com/accessible-ai-blog Follow: William Falcon: https://twitter.com/_willfalcon https://www.williamfalcon.com Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani. You can expect weekly episodes every available as Video, Podcast, and blogposts. Intro track: Flow by LiQWYD https://soundcloud.com/liqwyd