Some people ask me where I get my newsworthy tech stuff: I’d say a large part of it is from podcasts. Usually, I listen to them when I’m doing some monotonous activity— jogging, walking to work, doing groceries, etc. They allow me to learn new things and turn my unknown unknowns into known unknowns.1 Plus, it’s a great way to add some sound in my painfully quiet room!
In this post, I’ll talk about five (5) podcasts I regularly follow (in no particular order):
- Talk Python to Me (Python). TPTM is probably one of the best Python podcasts around. For each episode, a guest comes in and talks about their Python journey, things they’ve built, and future directions of their work. The host, Mike Kennedy, gives really insightful discussions (and also a friendly guy on Twitter). If you’re a data scientist, web developer, or a Python newbie, there’s a TPTM episode for you. With that said, I highly recommend listening to this podcast.2
- Hanselminutes (Technology). Scott Hanselman is definitely one of my engineering pegs: generally fun guy who’s there to build and teach. This is probably one of the entries where you follow the person more than the podcast itself.3 He talks about a range of topics: software development, .NET, tech-in-general, etc. so you’re sure there will always be something to interest you. To be honest, listen to each episode even if you don’t know what’s it about, he’s really good at fleshing out the core meaning of a technology.
- This Week in Machine Learning and Artificial Intelligence (Machine Learning). I think there’s only a small number of high-quality machine learning podcasts around. As an ML practitioner, I think that TWiML provides you in-depth machine learning stories pass the hype. The host is well-informed and asks questions that dive into the ideas his guests present. In particular, I like his discussion on ML platforms, for it gives you a sense on how machine learning should be done at scale.
- Software Engineering Daily: Machine Learning (Machine Learning in Software Engineering Context). As someone who’s doing ML in the industry, software engineering plays a large part on how we deploy things. This podcast actually goes into different software engineering topics, but the link I provided is an archive for all their ML-related episodes. If you’re interested in various ML-related open-source tech (Tensorflow, Kubeflow, Docker, etc.), then this podcast will be perfect for you!
- Code Newbie Podcast (Beginner-friendly programming). As a programmer, I’m a professional amateur.4 I know some things, but there are definitely a lot of things I’d still scratch my head on. Code Newbie talks about different developer journeys, and how someone learned their way in this field. This podcast will really inspire you to become better, and accepts you no matter what programming-level you are on.5
Other podcasts I listen to occasionally:
- Test and Code: good resource to learn about different software testing tools and principles.
- Talking Machines: another well-produced podcast geared for more academic machine learning researchers. Neil Lawrence is fantastic. Listen to his episode on ML and Society.
- Google Cloud Platform Podcast: we use GCP at work, so this is a nice resource.
- Changelog: really good podcast on open-source and general software development. I’d recommend listening to, albeit retired, Request For Commits if you care about open-source.
- 10% Happier Podcast with Dan Harris: a podcast on meditation and living a happier life.
- Art of Manliness: title sounds pure broetry, but content is really insightful for self-development. Includes talks that encourages men to become better sons, brothers, fathers, and husbands in their life.
- History of Rome: one of the best history podcasts that lets you travel from the times of the Roman Kingdom, to the Republic, to the Empire, and to its inevitable fall.
- That’s so many podcasts! How do you listen to them all? I definitely can’t and to be honest I have a backlog of episodes to listen to. The key is not to be overburdened by too much information. Just listen when you can: you do this for leisure, not for work.
- When do you listen to podcasts? I don’t have time for that! I listen when I’m doing something routine: walking to work (~15 minutes), jogging (~45 minutes), grocery (~1 hr). It’s more on passive listening, just like turning on the radio, only difference is that you can curate what you hear.
- What apps do you use? Right now it’s just Apple Podcasts. It works out of the box and serves me well. I load the episodes in my phone and just listen to them while travelling.
- Talk more about turning your unknown-unknowns into known-unknowns I’d probably dedicate another post for that.
Based on Donald Rumsfeld’s quote: “There are known knowns. There are things we know that we know. There are known unknowns. That is to say, there are things that we now know we don’t know. But there are also unknown unknowns. There are things we do not know we don’t know”. There’s also a good paper that maps this into the experience of scientific inquiry. ↩
I got this from Scott Hanselman, although I have a different interpretation: the idea is that as we go through our careers and develop experiences, we become really good at becoming beginners. For example, right now I’m a total beginner at Go, but I’d say I’m a better beginner right now (with my experience) than I’d be if I’m learning Go five years ago. Right now, I already have a framework and (hopefully good) conceptual strategy if I want to learn something new. Still an amateur, but I do it professionally. ↩
The host, Saron Yitbarek, also has a well-produced podcast called Command Line Heroes. It’s really worth listening to if you want to dig deep on how tech evolved (from open source to agile methodologies and to the cloud)! ↩