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Ken Jee


The Ken's Nearest Neighbors Podcast is about telling the unique stories of the people in the data and AI space. In highly technical fields, we often lose sight of the individuals who are making the positive change. The podcast focuses on who these people are and how they have approached the big decisions in their life that shaped their world view and career. While the podcast is centered on a technical domain, the conversations often touch on personal philosophy, the pursuit of meaning, and how we define success in our career and lives.


Ken's Nearest Neighbors

KNN EP. 01 - This is the first episode of the Ken Jee podcast (Now renamed Ken's Nearest Neighbors)! I talk about who I am, what you can expect from the podcast, and why you'll want to stay tuned for future episodes.

So what is this new podcast thing I’m doing? To put simply, this podcast is a more formalized version of the interviews that I have been doing on my channel for some time now. I wanted to make them easier to listen to on the go and bring you all increasingly exciting and diverse guests. 

If you aren’t familiar, my name is Ken Jee and I am the head of data science at a sports analytics consulting firm. I am probably better known for my youtube channel though. A staple of my career has been learning through examples. I think there is tremendous power in stories, and this podcast was formulated to bring the most interesting stories I could find about data science, sports analytics, productivity and learning philosophy straight to your ears. Hopefully, I will have the opportunity to bring in some of my idols from data science, sports, and maybe even the authors from some of the books that I’ve read. 

This first podcast episode is named “who am I?” because I have yet to come up with a name. I thought it would be awesome to have the various communities that I am a part of come up with a fitting title. The winner will get a shout out, 30 minutes of my time for data science advice (or just to chat), and a prize based on their region. Comment below with a name, on the twitter post, or on my community post which I have linked below. Hint: I like puns. I would love for you all to be involved in this endeavor with me! 

This podcast will be available on all of the main channels, spotify, apple podcats, etc. and will also have its dedicated youtube channel. I will also have a podcast clips channel for if you only want the juiciest of clips and hottest of takes. 

The first 10 or so episodes will be bulk uploaded at the beginning of November. These are duplicates of the interviews on my youtube channel. From there, it will be a fresh episode every week only available on the platforms I’ve mentioned before. I highly encourage guest recommendations, topics, and feedback to make this the best platform possible. 

Again, thank you for tuning in, and I look forward to learning with you on this fun new journey!

Hello World. Who am I? - KNN Ep. 01

We finally have a name! Ken's Nearest Neighbors was proposed by Cillian Raftery, and was an easy choice. It was the most requested name by popular demand, and it was the best fit with the mission of the podcast. 

We are happy to announce Ken's Nearest Neighbors to the world!

Notorious KNN - KNN Ep. 1.5

KNN Ep. 02 - In this episode I interview my friend Tim Bowling who transitioned from a NASA Physicist to a Data Scientist.

Tim's work focused on simulating asteroid collisions and understanding the possible impacts that these could have on planet habitability. 

Before entering data science, he attended a data science boot camp in Chicago called metis. He believes that these could be helpful for some people entering the field, but not for everyone. 

I talk with Tim about his expectations about data science versus reality, and about how his previous experience have made him successful in the field. 

We also talk at length about what someone who is new to data science should do to achieve success in their first position in the field.

NASA Physicist Turned Data Scientist (Tim Bowling) - KNN Ep. 02

In this episode, I talk with @DataScienceJay about how to get a data science job at a FAANG Company (Facebook, Amazon, Netflix, Google) and bay area startups. Jay has worked as a data scientist at multiple data science startups in the bay area and has started interviewquery.com. He has a tremendous amount of experience with the FANG interview process and on his youtube channel he has multiple mock interviews with real technical questions from these companies.

How to Land a Data Science Job at FAANG (Jay Feng) - KNN Ep. 03

In this episode I talk with Jaemin Lee (Import Data) about if you should major in data science. Jaemin switched his major from CS to data science and recently landed a job as an entry level data scientist. He talks about his experience with his major, interviewing for data science jobs, and with creating content through youtube.

Should You Major in Data Science? (Jaemin Lee) - KNN Ep. 04

In this episode I interviewed Daniel Bourke, a content creator and machine learning engineer. I get his take on learning machine learning and data science and taking an experimental approach to life. 

Daniel's Channel: https://www.youtube.com/channel/UCr8O8l5cCX85Oem1d18EezQ
Project From Sratch: https://www.youtube.com/playlist?list=PL2zq7klxX5ASFejJj80ob9ZAnBHdz5O1t
Resume Reviews: https://www.youtube.com/playlist?list=PL2zq7klxX5ARwEq13TVSxcKmx6pVv2R2B
2020 Roadmap: https://www.youtube.com/watch?v=pHiMN_gy9mk

Uber Driver to Machine Learning Engineer in 9 Months (Daniel Bourke) - KNN Ep. 05

In this episode, I spoke with Danny Ma about value and mentorship in data science. Danny progressed from humble beginnings in data entry all the way to starting his own data science consulting company. Danny also has a tremendous social reach through linkedin and loves mentoring people interested in the field. 

Danny's Channel: https://www.youtube.com/channel/UCGYPQz_qySbPESTK8k2ky5g
Danny's Linkedin: https://www.linkedin.com/in/dannykcma/

Should You Have a Data Science Mentor? (Danny Ma) - KNN Ep. 06

In this episode I had the privilege of speaking with Anima Anandkumar about the her background, her work at NVIDIA, and how she views the future of Machine Learning and AI. 

Anima is the Head of ML and AI research at NVIDIA. She also is a Bren Professor at CalTech. She has been honored by multiple organizations for her contributions to the field of AI research and she has given multiple talks on topics ranging from the future of AI to ethics in the data science community.

Her Ted Talk: https://www.youtube.com/watch?v=zkJ5lEuGQDw
Her YouTube Channel: https://www.youtube.com/user/animakumar82
Her Twitter: https://twitter.com/AnimaAnandkumar

What is the Future of AI at NVIDIA? (Anima Anandkumar) - KNN Ep. 07

In this episode, I had the pleasure of speaking with Nick Wan. Nick streams data science content on twitch, but also has worked in sports analytics with the Cincinnati Reds. His work there allowed him to pivot recently into a data science manager role at KFC.

In this interview I talked with Nick about his experiences learning data science, breaking into sports analytics, and streaming data science content on Twitch. He also gives some awesome advice related to interviewing for data science roles and learning as you go. At around an hour in Nick and I talk about what our projects look like and how they have grown over time. Here I even bring up some of my grad school work as an example. If you want to see the video version of the podcast so you can see what Nick and I are referencing check out the Youtube video here: https://www.youtube.com/watch?v=S_CuB__nsmI.

Follow Nick on Twitch: https://www.twitch.tv/nickwan_datasci
Follow Nick on Twitter: https://twitter.com/nickwan

The Data Science Twitch Streamer + Sports Analytics (Nick Wan) - KNN Ep. 08

In this episode I interviewed Abhishek Thakur. He is the first ever 3-time and 4-time kaggle grand master. Abhishek takes us inside his unique mind to understand how he performs so well in the kaggle competitions.

He also talks about how he got his first data science job, the importance of data science projects, and also about getting a job in another country.

Abhishek's Youtube: https://www.youtube.com/channel/UCBPRJjIWfyNG4X-CRbnv78A
His new book: https://amzn.to/2YBxGcu

Inside the Mind of the ULTIMATE Kaggle Grandmaster (Abhishek Thakur) - KNN Ep. 10

I had the pleasure of interviewing Eugene Yan. he works at the intersection of machine learning and product to build pragmatic, customer-facing ML systems. He also writes & speaks about effective data science, data/ML systems, and career growth.
Currently, He is an Applied Scientist at Amazon shipping ML and recommends systems to help customers read more.
On his website, he shares what he’s learned on shipping ML systems, with a pragmatic and product slant. He’s written 119 posts and 215,291 words so far! 
In this episode, we learn about how Eugene broke into data science from a psychology background. We also go through the challenges of breaking into the US job market. I learned quite a bit about the visa process and how different countries can have different visa quotas. Finally, we touch on the importance of end to end data science and how sharing your work can help you to make your own luck. I had a great experience getting to know Eugene better through this interview, and I hope you learn a lot from this episode!

What are The Skillsets Needed to be an Effective Data Scientist (Eugene Yan) - KNN Ep. 48

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