Chai Time Data Science
A podcast by Sanyam Bhutani
149 Episodes
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Top Kagglers Panel on Best Practises for Training Models
Published: 22/01/2023 -
Announcement + Amed Coulibaly | How to become Kaggle Competitions Grandmaster | #159
Published: 29/12/2022 -
Jeremy Howard interviews Kaggle Grandmaster Sanyam Bhutani | #150
Published: 23/03/2022 -
Kathleen Walch, Ronald Schmelzer: AI Today Podcast, Creating AI Content: #137
Published: 6/10/2021 -
ACM RecSys Winning Solution: Benedikt Schifferer, Bo Liu, Chris Deotte, Even Oldridge #136
Published: 31/07/2021 -
"SentDex", Harrison Kinsley: YouTube, Entrepreneurship and NNFS.io #135
Published: 23/07/2021 -
Clair Sullivan: Graphs and the Neo4J Ecosystem #134
Published: 20/07/2021 -
Emil Wallner: Art & ML, Being Internet Taught, Creating ML Content #133
Published: 7/01/2021 -
Andrada Olteanu: Learning Data Science, Journey to becoming Kaggle Master #132
Published: 3/01/2021 -
Laura Leal Taixé: Computer Vision & Research at the Dynamic Vision & Learning Group #131
Published: 31/12/2020 -
William Falcon: The PyTorch Lightning Story #130
Published: 27/12/2020 -
Katy Warr: Fooling AI, Strengthening Deep Neural Networks Book, Adversarial Attacks #129
Published: 24/12/2020 -
Laura Fink: Journey to becoming Kaggle Kernels Grandmaster #128
Published: 20/12/2020 -
Barr Moses: Data Reliability, Data Downtime, MonteCarlo Data #127
Published: 17/12/2020 -
David Luebke: Graphics Research at NVIDIA, Training GANs with Limited Data #126
Published: 13/12/2020 -
Torsten Sattler: CV, Mixed Reality, Localisation & Robotics #125
Published: 10/12/2020 -
Zachary Mueller: Learning, Applying and contributing to Fastai #124
Published: 6/12/2020 -
Arsha Nagrani: Multi-Modal Research, Speaker Diarisation, VoxCeleb #123
Published: 3/12/2020 -
Ekaterina Kochmar: Automated Language Teaching & Assessment, NLP, Korbit.ai #122
Published: 29/11/2020 -
Richard Craib: The Numerai Story, Building the World's last Hedge Fund #121
Published: 26/11/2020
Chai Time Data Science show is a series where Sanyam Bhutani interviews his Data Science Heroes: Practitioners, Kagglers & Researchers about all things Data Science