Kevin Systrom is the co-founder and former CEO of Instagram. In this episode we talk about his time after leaving the company, whether becoming a billionaire made him happier, how to decide what to work on, the Japanese concept of Ikigai, or a reason for being, and meditation. We then dive into his current project -- rt.live -- a website which tracks the spread characteristics of COVID-19. The statistical model underlying the website is Bayesian and built using PyMC3. Kevin shares why he chose that approach and how he got started on PyMC3. Show notes Kevin Systrom on Twitter and his blog Instagram Ikigai: The Japanese Secret to a Long and Happy Life The Mind Illuminated COVID-19 tracking: https://rt.live An Intuitive Guide to Bayesian Statistics PyMC3 Statistical Rethinking by McElreath Bayesian Methods for Hackers by Cam Davidson-Pilon Special thanks to all my patrons, specifically Jonathan Ng, Richard Craib, Daniel Gerlanc, and Ayan Doss. Support the show

In this episode I talk with Jeremiah Lowin, founder and CEO of Prefect, the company behind the open-source dataflow automation tool of the same name. We first dive into his background in risk management and his frustrations behind trying to automate certain tasks using the currently available tools. This inspired him to write Prefect, an open-source dataflow automation tool for Python which focuses on the data scientist's needs. We go on to discuss his decisions and experiences in founding a company with a significant portion of the software being open-source. Finally, Jeremiah explains how COVID-19 has caused him to question everything he thought he knew about his business and decide to open-source even more of his company's software stack. He shares his insights and experiences of how other startups can turn this challenge into an advantage and how to overcome the challenges of all employees switching to remote-only. Links: https://twitter.com/jlowin https://www.prefect.io/ https://github.com/PrefectHQ/prefect https://tandem.chat/ Special thanks to my patrons: Ayan Doss Daniel Gerlanc Richard Craib Jonathan Ng If you would like to support the podcast, you can do so here: https://www.patreon.com/twiecki Support the show

In this episode I talk with Matt Rocklin. Matt is best known for his work on Dask, a parallel computing package built into the PyData stack. After working on open source software at Anaconda and NVIDIA he now founded his own company centered around Dask called Coiled Computing. In this episode we talk about the insights into open source he gained through his career, what Dask is and how it is funded, and then of course his new company. Links: https://twitter.com/mrocklin https://dask.org https://coiled.io https://matthewrocklin.com https://rapids.ai https://pangeo.org https://prefect.io Thanks to my Patrons for their support, especially: Daniel Gerlanc Richard Craib Jonathan Ng Support me here to get early access: https://www.patreon.com/twiecki PyData is a registered trademark of NumFOCUS, Inc. Support the show

Let's welcome the new year with a new episode of the PyData Deep Dive. In this episode I talk to Travis Oliphant: Founder of Anaconda Inc and Quansight Inc, as well as the creator of NumPy. In this episode Travis takes us from the early days of NumPy up to the current state and future of the PyData ecosystem and how Quansight is contributing to that future. Special thanks to my Patreons Andrew Ng, Daniel Gerlanc, and Richard Craib. If you would like to support the podcast go to: https://patreon.com/twiecki Follow Travis on Twitter: https://twitter.com/teoliphant Follow me on Twitter: https://twitter.com/twiecki Support the show

I am beyond excited to share this first episode of the PyData podcast with you. The idea is to have a free-form discussion with interesting guests which does not shy away from more advanced topics. In this episode I talk to Chris Fonnesbeck: Professor for biostatistics at Vanderbilt University and, as of recent, Data Scientist at the New York Yankees. We start off this discussion by talking about Bayesian statistics, probabilistic programming. Chris then talks about the history of PyMC and what the current status of PyMC4 is. We then dive more into his background and how he moved from marine biology to become a data scientist in sports analytics and the lessons he learned along the way. Special thanks to my Patreons Andrew Ng, Daniel Gerlanc, and Richard Craib. If you would like to support the podcast go to: https://patreon.com/twiecki Follow Chris on Twitter: https://twitter.com/fonnesbeck Support the show