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    Technology

    Chai Time Data Science

    Chai Time Data Science show is a series where Sanyam Bhutani interviews his Data Science Heroes: Practitioners, Kagglers & Researchers about all things Data Science

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    Copyright: © Sanyam Bhutani

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    Latest Episodes:
    02: fast.ai Lesson-2 Production & SGD From Scratch | fast.ai 2019 & Things Jeremy Howard says to do Mar 07, 2020
    Show notes

    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


    03: fast.ai Lesson-3 Multi-label; SGD from scratch | fast.ai 2019 & Things Jeremy Howard says to do Mar 07, 2020
    Show notes

    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


    00 fast.ai 2019 Summaries & Things Jeremy Howard says to do Mar 07, 2020
    Show notes

    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


    01 fast.ai Lesson-1 Image Classification | fast.ai 2019 & Things Jeremy Howard says to do Mar 07, 2020
    Show notes

    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


    Interview with Marios Michailidis | What does it take to become #1 on Kaggle | DSB 2019, 14th Pos Sol Mar 05, 2020
    Show notes

    Previous Interview Link: https://sanyambhutani.com/interview-with-kaggle-competitions-grandmaster--kazanova--rank--3---dr--marios-michailidis/

    Chai Time Data Science Playlist: https://www.youtube.com/playlist?list=PLLvvXm0q8zUbiNdoIazGzlENMXvZ9bd3x

    In this episode, Sanyam Bhutani interviews Kaggle Legend, GM: Marios where they continue talking a lot about Kaggle and how Kaggle has helped Marios in his data science journey, and his data science work at H2O.ai, all about the projects where he is contributing to.

    They also discuss his recent gold winning solution to the data science bowl 2019 competition, the approaches shared by Marios are applied, even generally, outside of that competition.

    They also touch upon a very important topic that isn't discussed as much on this podcast, the personal side of things, and the personal sacrifices it takes to really become the best become the best in the world become the best on Kaggle, like the sacrifices it took Marios to become number one on Kaggle both in competitions and discussions.

    Links:

    Solution by Marios' team: https://www.kaggle.com/c/data-science-bowl-2019/discussion/127221

    DSB 2019 Competition: https://www.kaggle.com/c/data-science-bowl-2019/overview

    H2O blog: https://www.h2o.ai/blog

    Driverless AI: https://www.h2o.ai/products/h2o-driverless-ai/

    Follow:

    Marios Michailidis:

    https://twitter.com/stacknet_?lang=en

    https://www.linkedin.com/in/mariosmichailidis/

    https://www.kaggle.com/kazanova

    Sanyam Bhutani:

    https://twitter.com/bhutanisanyam1

    Blog: sanyambhutani.com

    About:

    http://chaitimedatascience.com/

    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.

    Flow by LiQWYD https://soundcloud.com/liqwyd


    Interview with fast.ai hero: Radek Osmulski | Fast.ai, Learning to Learn | Machine Learning, Kaggle & Blogging Mar 01, 2020
    Show notes

    Video version available here: https://youtu.be/4h41v07bYYI

    Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani

    In this episode, Sanyam Bhutani interviews a machine learning hero to the complete fast.ai: Radek Osmulski.

    Personal Note: I think this is one of the most honest, and the best interviews in terms of the transparent Kaggle, learning to learn, and how to approach machine learning problems or machine learning materials advice.

    Radek shares his journey with complete honesty about how he went about learning the fast.ai materials, how he went on to smashing the kaggle competitions that he participated in, and his journey on learning to learn about all of the materials fast.ai and beyond in the machine learning world.

    They also talk a lot about learning to learn fast ai, and Kaggle all three together and individually as well.

    Follow:

    Radek:

    https://twitter.com/radekosmulski

    https://medium.com/@radekosmulski

    https://www.kaggle.com/radek1

    https://www.linkedin.com/in/radek-osmulski-6b935794/?originalSubdomain=pl

    Sanyam Bhutani:

    https://twitter.com/bhutanisanyam1

    About:

    http://chaitimedatascience.com/

    A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.

    You can expect weekly episodes every Sunday, Thursday available as Video, Podcast, and blogposts.

    If you'd like to support the podcast: https://www.patreon.com/chaitimedatascience

    Intro track:

    Flow by LiQWYD https://soundcloud.com/liqwyd


    Interview with Dr. Ashrith Barthur | Cyber-Security & Anti-Money Laundering | Applied AI & H2O AI Feb 27, 2020
    Show notes

    Chai Time Data Science Playlist: https://www.youtube.com/playlist?list=PLLvvXm0q8zUbiNdoIazGzlENMXvZ9bd3x

    In this episode, Sanyam Bhutani interviews Dr. Ashrith, Chief Security Scientist at H2O.ai

    As you can guess, they talk all about cybersecurity and AI, AI broadly speaking in this episode. Ashrith has a background in cyber security and has done a lot of interesting research in the field, he's also currently doing applied research at H2O.ai.

    This is a first on this podcast series: They discuss about cybersecurity generally speaking, and its applications in AI, including anti money laundering and the applications that H2O is working on in the cybersecurity domain.

    Links:

    Webinars: https://www.h2o.ai/webinars/

    H2O blog: https://www.h2o.ai/blog

    Driverless AI: https://www.h2o.ai/products/h2o-driverless-ai/

    Follow:

    Ashrith Barthur:

    https://twitter.com/cyberbaggage

    https://www.linkedin.com/in/abarthur/

    Sanyam Bhutani:

    https://twitter.com/bhutanisanyam1

    Blog: sanyambhutani.com

    About:

    http://chaitimedatascience.com/

    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.

    Flow by LiQWYD https://soundcloud.com/liqwyd


    Interview with Sebastian Raschka | Statistics, Open Source & ML Research | Python for ML Book Feb 23, 2020
    Show notes

    Video Version available here: https://youtu.be/beSLA-wO2T4

    Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani

    In this episode, Sanyam Bhutani interviews Dr. Sebastian Raschka, currently an assistant professor of Statistics at University of Wisconsin, Madison and the Author of Python for machine learning book.

    Sebastian has a background in biology and holds a PhD in quantitative biology, biochemistry, and molecular biology.

    In this interview, they talk all about his journey into the intersection of biology, machine learning, statistics, open source, and machine learning research. Yes, these are all of the topics that Sebastian is currently involved in.

    They also talk about his journey with writing the book and also discuss the his current research interests and his research efforts.

    They talk about another area that Sebastian is also active in, which is open source. Sebastian is an assistant professor at UW but he shares advices that apply to any student at university or otherwise in the field of machine learning looking to learn anything.

    Links:

    Python for ML Book: https://sebastianraschka.com/books.html#python-machine-learning-3rd-edition

    Research: https://scholar.google.com/citations?user=X4RCC0IAAAAJ&hl=en

    Follow:

    Sebastian Raschka:

    https://twitter.com/rasbt

    https://github.com/rasbt

    https://www.linkedin.com/in/sebastianraschka/

    https://sebastianraschka.com

    Sanyam Bhutani:

    https://twitter.com/bhutanisanyam1

    About:

    http://chaitimedatascience.com/

    A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.

    You can expect weekly episodes every Sunday, Thursday available as Video, Podcast, and blogposts.

    If you'd like to support the podcast: https://www.patreon.com/chaitimedatascience

    Intro track:

    Flow by LiQWYD https://soundcloud.com/liqwyd


    Navdeep Gill | Software Engineering & Data Science | Machine Learning Interpretability | Open Source Feb 20, 2020
    Show notes

    Chai Time Data Science Playlist: https://www.youtube.com/playlist?list=PLLvvXm0q8zUbiNdoIazGzlENMXvZ9bd3x

    In this episode, Sanyam Bhutani interviews Navdeep Gill: Senior Data Scientist and Software Engineer at H2O.ai.

    In this interview, they talk all about the intersection of these two fields: data science and software engineering, best practices for both data science and software engineering and how much of software engineering skills should our data scientists really know, is the question that they also discuss in this interview.

    They talk all about Navdeep's journey into machine learning, machine learning interpretability and his journey at H2O.ai.

    They also talk a lot about machine learning interpretability, Navdeep's thoughts on it, as well as MLI inside of H2O's products.

    Links:

    An Intro to MLI Book: https://www.h2o.ai/wp-content/uploads/2019/08/An-Introduction-to-Machine-Learning-Interpretability-Second-Edition.pdf

    Driverless AI:

    https://www.h2o.ai/products/h2o-driverless-ai/

    H2O-3:

    http://docs.h2o.ai/h2o/latest-stable/h2o-docs/welcome.html

    Follow:

    Navdeep Gill:

    https://twitter.com/Navdeep_Gill_

    Sanyam Bhutani:

    https://twitter.com/bhutanisanyam1

    Blog: sanyambhutani.com

    About:

    http://chaitimedatascience.com/

    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.

    Flow by LiQWYD https://soundcloud.com/liqwyd


    Interview with Zachary Mueller | Fast.ai: The course and New Library | SGs and Top Down Learning Feb 16, 2020
    Show notes

    Video Version available here: https://youtu.be/AXr8pzXXUDQ

    Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani

    Correction: Apologies and correction: Zach is a student at the University of West Florida, not university of Washington

    In this episode, Sanyam Bhutani interviews his peer from the fast.ai community: Zachary Mueller, who's a student at the University of West Florida, currently pursuing his bachelor's degree in software design and development.

    In this interview they talk all about fast.ai the course and fast.ai V2 the upcoming library along with all about Zach's experience with fast.ai, his journey into deep learning and fast.ai, and the projects that he's built while going through the course.

    They also talked about a study group that Zach has now been running for a few weeks, that builds on top of fast.ai V2 the new library on which the course is yet to come out.

    They also talked a lot about the top down learning approach and how can you go about learning fast.ai.

    Links:

    Study Group by Zach: https://forums.fast.ai/t/a-walk-with-fastai2-study-group-and-online-lectures-megathread/59929

    Practical-Deep-Learning-for-Coders-2.0: https://github.com/muellerzr/Practical-Deep-Learning-for-Coders-2.0

    Zach's YouTube Channel: https://www.youtube.com/channel/UCmKoQOD8uBqsRS8XDdSgrlQ

    Follow:

    Zachary Mueller:

    https://twitter.com/TheZachMueller

    Sanyam Bhutani:

    https://twitter.com/bhutanisanyam1

    About:

    http://chaitimedatascience.com/

    A show for Interviews with Practitioners, Kagglers & Researchers and all things Data Science hosted by Sanyam Bhutani.

    You can expect weekly episodes every Sunday, Thursday available as Video, Podcast, and blogposts.

    If you'd like to support the podcast: https://www.patreon.com/chaitimedatascience

    Intro track:

    Flow by LiQWYD https://soundcloud.com/liqwyd


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