Ken's Nearest Neighbors

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_qySbPESTK8k2ky5gDanny's Linkedin: https://www.linkedin.com/in/dannykcma/

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/UCr8O8l5cCX85Oem1d18EezQProject From Sratch: https://www.youtube.com/playlist?list=PL2zq7klxX5ASFejJj80ob9ZAnBHdz5O1tResume Reviews: https://www.youtube.com/playlist?list=PL2zq7klxX5ARwEq13TVSxcKmx6pVv2R2B2020 Roadmap: https://www.youtube.com/watch?v=pHiMN_gy9mk

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.

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. 

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.

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! 

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!