In this episode, we are joined by Kunal Gandhi, CEO of SimpL.

 Technology and AI are making their way into modern fitness programs by giving users more access to their data and not limiting use to high-end memberships.  Kunal's company, SimpL, is an AI personal trainer that analyzes your form when you exercise and gives you real-time audio feedback. We discuss using pose-estimation and computer vision to track the user while they are excersing. Also, Kunal talks about changing the narrative around exercise on and off the field. Finally, he highlights the importance of resilience in achieving your goals and how keeping it in mind has helped him launch SimpL off the ground.

 Download SimpL on the Apple App Store HERE [https://apps.apple.com/us/app/simpl-ai-personal-trainer/id1524733232]

Find Open Positions at SimpL HERE [https://www.linkedin.com/company/simplfit/jobs/]

Check out the TWR Podcast on:
Instagram HERE [https://www.instagram.com/theweeklyregression/]
Twitter HERE [https://twitter.com/TheWeeklyReg]
LinkedIn HERE [https://www.linkedin.com/company/the-week]

In this episode, we are joined by Guillermina Sutter Schneider, a Project Manager at the CATO Institute.

What’s the point of using data if the average person cannot understand your results? Not only is Guillermina transforming Latin American policy, but she is also an expert at communicating her analytic results through dynamic visualizations that appeal to everyone. We discuss the Human Freedom Project at CATO and the need for visualizations, especially when multiple data streams are being ingested. Likewise, we talk about ways to visualize your ML and AI models to optimize performance and gain valuable insight. 

Finally, Guillermina highlights enjoying your data journey and being patient when learning new skills or operating in a new domain.

Follow Guillermina on Twitter HERE [https://twitter.com/gsutters?s=20]

Check out the TWR Podcast on:

Instagram HERE [https://www.instagram.com/theweeklyregression/]

Twitter HERE [https://twitter.com/TheWeeklyReg]

LinkedIn HERE [https://www.linkedin.com/company/the-weekly-regres

In this episode, we are joined by Amir Mehrbakhsh, a Consultant at Reference Point.

 The credit score is a metric that has been around for quite some time and is used as a way to understand a person's financial behavior.  However, the predictive model behind the score is pretty simple and does not take into account many variables in a person's financials or life. 

Amir is a fintech and startup enthusiast analyzing how various technologies are changing the way we live our daily lives. In a publication of his, he outlines the concept of "Credit Worthiness" and how a more general AI model can actually predict a person's financial behavior using a multitude of variables across a variety of personas. Also, we briefly talk about the ethical implications of adopting the output of a model that many people do no understand.  Finally, Amir talks about how to get involved in the Data and AI world without a technical background. 

Find Amir's other insightful articles on:
 Medium HERE [https://medium.com/@amirmehrbakhsh]
LinkedIn HERE [https://www.linkedin.com/in/amir-mehrbakhsh-83581869/] 

Check out the TWR Podcast on:
  Instagram HERE [https://www.instagram.com/theweeklyregression/]
  Twitter HERE [https://twitter.com/TheWeeklyReg]
  LinkedIn HERE [https://www.linkedin.com/company/the-weekly-regression]

In this episode, we are joined by Dan Vitale, a Data Scientist at Datatechnica International.

 Have you ever wondered where your ancestors come from and how that might affect your health? Through his work at the National Institute of Health (NIH), Dan is able to tap into a patient's DNA to detect their ancestry and early signs of genetic diseases. At a country-specific level, Dan can visualize how certain genes vary amongst populations and show why certain groups of people are more likely to have diseases than others. From the human body to a database, Dan breaks down how he is able to acquire genetic data in the first place and the methods used to calculate ancestral groups.  Finally, he underscores the importance of domain experience to help guide project and model development.

 Follow Dan on Twitter HERE [https://twitter.com/dan_vitale_]

 Check out the TWR Podcast on:
 Instagram HERE [https://www.instagram.com/theweeklyregression/]

 Twitter HERE [https://twitter.com/TheWeeklyReg]

 LinkedIn HERE [https://www.linkedin.com/company/the-weekly-regression/ 

In this episode, we are joined by Mary Gibbs, a Data Scientist at Mosaic Data Science.

  Although Mary's data journey is in biological sciences, she is able to build, train, and deploy any Data Science solution or Machine Learning application no matter the domain. From the initial meeting with the client all the way to the final product, Mary breaks down her process of developing an appropriate solution given a client's domain and technical constraints. Finally, she gives her advice to anyone interested in or just starting their own data journey, where she emphasizes the importance of data science projects on the side to gain experience rather than relying on online courses, boot camps, and degrees.

  Check us out on Instagram HERE [https://www.instagram.com/theweeklyregression/]
  Twitter HERE [https://twitter.com/TheWeeklyReg]
  LinkedIn HERE [https://www.linkedin.com/company/the-weekly-regression/]

Welcome to The Weekly Regression! Every Wednesday, starting February 10th, we will be interviewing data practitioners and leaders who are working on groundbreaking projects in Data Science, Machine Learning, and Artificial Intelligence. For listeners who are interested in data or just starting out in the data world, our guests will be simplifying the complex systems they use to transform and disrupt their respective fields

Follow us on Instagram HERE ( https://www.instagram.com/theweeklyregression/ )

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