Data Science Imposters Podcast

Latest Episodes:

Casual Talk, Space, and Bitemporal Tables Jul 26, 2021

Show notes

Jordy and Antonio meet after a vacation haitus or two. They talk space, life, and are even able to sneak in some data science.

If you’d like to see our show continue, reach out to the hosts.

3 Projects That Can Make You a Household* Name Jun 08, 2021

Show notes

*Household name is a bit of exaggeration – but certainly a known name in the ML community.

Today we are joined by Alex Beutel, KDD Cup co-chair and senior staff research scientist & tech lead / manager at Google to discuss the three projects for this year’s KDD Cup. It’s amazing the diversity in these projects and possible ways to solve it. Even if you didn’t get a chance to officially enter the competition this year, think about how you would solve it, and then listen to how the winners of the contest were able to achieve top scores.

These are the three projects that we discuss during the show:

“… KDD 2021, the longest running and largest interdisciplinary conference on data science where the biggest names in the industry and academia come together to drive innovation in AI, machine learning, computer vision and more. Originally planned to take place in Singapore, the conference will be 100% virtual this year. As an added bonus, organizers will offer key content twice, on eight-hour intervals to ensure equitable access across time zones.”

Okay, I borrowed that last part from one of their press releases but if you don’t know KDD, you better ask somebody.

‘Data Science’ is an evolution. What does it mean now in the Workplace? w/ Erin Stanton May 31, 2021

Show notes

We didn’t always have ‘Data Science’ but we’ve had data for ever. We’re joined by Erin Stanton to learn about the evolution of Data Science in her work and personal life.

Erin Stanton has 13+ years of experience in big data and data science and she currently runs the Global Client Support organization for Virtu Analytics. Erin is known for her big energy which she brings to everything she does and has been more recently championing potential machine learning and AI techniques to answer client questions within her day job following her recent completion of her Masters in Data Science from UC Berkeley.

What are NFTs and why do you care? (Fixed episode link) Mar 29, 2021

Show notes

Shain and Calvin join us to tell us all about NFTs. NFTs stand for non-fungible tokens – meaning they represent unique items – unlike currency which is fungible and can be aggregate or divided.

NFTs could become a bigger industry than digital currencies so will you be an early adopter or late comer?

I don’t get the vaccine rollout … is using tech for a vaccine appt immoral … Mar 09, 2021

Show notes

Antonio and Jordy are back at it. No guests, just the two hosts catching up after 3 months of relative silence. Antonio explains to Jordy why he is befuddled by the vaccine rollout … in addition, he asks whether the script he wrote to find a vaccine appointment is immoral …

We’d like to hear from you so please reach out.

Can you remember this? We talk memory with John Graham, Grandmaster of Memory, and USA Memory Champion Dec 28, 2020

Show notes

What would you remember if you had better memory? In this episode we speak to the 2018 USA Memory Champion and Grandmaster of Memory, John Graham aka memoryjohn.com.

As imposters, we have lots of questions. John answers them with the exactness that you’d expect from someone who continues to train their memory. John is a great coach and he’ll even run us through a mental exercise where we memorize something – listen and see if you can follow along.

If you’re interested about learning more, check out John’s website. You can also join Jordy and Antonio as they read Moonwalking with Einstein. Imagine what’s possible if you applied these techniques into 2021.

Math in Data Science with Professor Margot Gerritsen Dec 14, 2020

Show notes

Today we are joined by Professor Margot Gerritsen from Stanford University today to talk to us about Math in Data Science, Diversity in Data Science, and some of the ideas behind a Growth Mindset.

She is co-founder and co-director of the global Women in Data Science (WiDS) conference, reaching more than 120,000 participants annually in more than 60 countries and inspiring thousands of women around the world to pursue careers in STEM or data science.

If you haven’t seen Margot’s Stanford TedX Stanford talk, you should do so now. Also, the Women in Data Science (WIDS) Conference is taking place on March 8, 2021. Click on the link above for more details, follow WiDS on Twitter @WiDS_Worldwide, or check out their LinkedIn profile: https://www.linkedin.com/company/women-in-data-science-wids-at-stanford-university

Margot recommended the book Mindset by Carol S. Dweck, Ph.D. Antonio is already a few chapters in. Here’s the Goodreads link for you interested in learning more.

Additional details about Margot:

Margot Gerritsen, a prominent Stanford professor in her field who radiates a passion for the computational sciences, including data science. She is professor of energy resources engineering at Stanford, the former director of the Stanford Institute for Computational and Mathematical Engineering, and until recently, the senior associate dean at Stanford’s School of Earth, Energy & Environmental Sciences. Margot is also the Chair of the Board of Trustees of SIAM. She has spent nearly her entire lifetime using mathematics to solve a wide variety of complex problems, including reservoir modeling, coastal ocean flows, and sail design for America’s Cup yachts.

Discovering interesting rules: Association Rule Learning Dec 01, 2020

Show notes

We’ve been doing this podcast for over three years and I’m surprised that we had never come across and discussed the topic of association rules. Association rules is a mining technique that allows you to find rules in your data. It’s pretty intuitive when you see it but we were so surprised how hard it was to talk about during the show.

Some resources that we encountered to get our head around the topic:

We take a look at this example: http://www.saedsayad.com/association_rules.htm during our conversation
Association Rules: https://towardsdatascience.com/association-rules-2-aa9a77241654
mlxtend Association rules documentation and example: http://rasbt.github.io/mlxtend/user_guide/frequent_patterns/association_rules/
Extracting Rules from Medical Health Records: https://www.sciencedirect.com/science/article/pii/S1877050917319658
Association Rule Learning Wikipedia Article: https://en.wikipedia.org/wiki/Association_rule_learning

We know that talking about some of these topics is difficult and sometimes it’s hard to follow and sometimes we don’t actually convey the message easily. We hope that our conversations spark some ideas, ignite you to try some of the code yourself, or do your own research.

Please email us if our shows have spoken to you in way way or another. Also, the first person to email us will get a Data Science Imposters Podcast face mask.

Stock Market: Investing and Data Science Nov 17, 2020

Show notes

Jordy and Antonio talk about the stock market. They focus on the data behind the stock market movements and also how you can get started investing in the stock market. Whether you have never traded in the market, are a buy-and-hold investor, or are an avid investor – you’ll enjoy this spirited conversation that could have gone on for more longer.

We were excited to do this episode and when we were done, we realized that there’s so much more to talk about but we won’t know if we should or shouldn’t do a follow-up episode unless we hear from our listeners. We look forward to your feedback.

How Emerging Data Scientists Can Path Creative Careers (And How Employers Can Help Get Them There) Nov 02, 2020

Show notes

This episode is the panel discussion that we moderated two weeks ago for the Tom Tom Cities Rising Summit (https://www.tomtomfoundation.org/cities-rising-summit).

Here’s the description provided for the event: Join regional data science leaders for a discussion that will touch on best practices for college graduates to mid-career professionals who are seeking rewarding employment opportunities, as well as insights into how organizations can build the data science team that best suits their needs.

Listen to the perspective of these fantastic panelists: