Although listening to music has its moments, repeating the same songs over and over again can get tedious. With so many great podcasts out there though, there’s no reason why you can’t sub out your regular playlist for something a little more educational and insightful while you hit the gym or drive to work.
Podcasts have exploded in popularity over the last few years. According to Statista, almost 60% of all U.S. consumers above the age of 12 regularly listen to one. What’s more, the number of regular podcast listeners has more than doubled over the last decade. And with millions of podcasts to choose from, you are guaranteed to find something that suits your tastes.
As you surely know, the machine learning space is constantly evolving. It seems like there is a new development or breakthrough pretty much every week—and that’s because there is. The pace of change within the space is astounding.
While this is great news for model development and making new advances in the tech space, the prospect of keeping up can be daunting… especially when you are part of a busy ML team and have your own projects to keep on top of.
This is why we wholly recommend regularly listening to machine learning podcasts.
Outside of hitting the books and putting your skills into practice, one of the best and most convenient ways to keep your machine learning knowledge in shape is to listen. We know that selecting from the thousands of podcasts that are out there is no easy feat, though. That’s why we have put together our own list of favorites (in no particular order.)
Without further ado, here are eight podcasts that you should consider integrating into your listening pipeline to learn and gain new insights from the very best thought leaders and developers in the machine learning space.
The first podcast on our list of top podcasts for machine learning is called Data Skeptic. Although the name may sound a little funny, it is a highly regarded podcast in the ML space and has a huge listener base.
Although this podcast is geared more towards people who are just getting started with their learning, there’s plenty of content that ML veterans will find interesting, too. The podcast does a great job of both covering the basics and delivering high-level insights in short 10- to 15-minute episodes, which ensures that listeners’ minds don’t wander.
Don’t let the short lengths of these episodes put you off, though! Just because they are short does not mean that they are uninformative. Most podcast episodes cover and give you the lowdown on complex topics including MLOps, k-means clustering, and more. As an example, Data Skeptic has a podcast library covering the topic of interpretability, which gives both newbies and experts an in-depth look at how cutting-edge ML algorithms arrive at their conclusions.
This Week in ML & AI, also known as TWIML, is a popular podcast that began in early 2016. In just over five years, the podcast’s userbase has steadily grown and is now considered to be one of the leading podcasts in the field of artificial intelligence and machine learning, with almost 600 episodes at the time of writing.
TWIML averages two episodes per week, with each episode sharing insights from data scientists, AI researchers, and leaders in the tech, IT, and AI and machine learning spaces. The podcast is both delivered by and listened to by a range of people, from your average tech enthusiast to subject matter experts, which has allowed the team to create an innovative community that focuses on the exciting, real-world applications of AI and machine learning.
Some of TWIML’s more popular guests have included Kai-Fu Lee, Greg Brockman, Yoshua Bengio, and Gary Marcus.
Jay Shah is a computer science professional and Ph.D. student at Arizona State University. Shah is currently focusing his work on using deep learning models for biomarker discovery, specifically for Alzheimer’s disease and research into aging. His work also looks at developing interpretable AI models for healthcare applications.
Shah’s podcast interviews explore the many applications of machine learning in both industry and academia. Shah is particularly adept at making his podcast guests feel at ease during their time on the show, which enables him to pick their brains and reveal some of the more exciting and unusual developments n the ML space.
MLOps.community is one of the more focused podcasts which, as you have probably guessed, leans heavily on the operationalization aspects of machine learning. Not only is the MLOPs.community podcast one of the best resources to find other MLOps enthusiasts, but the team behind it release some of the very best MLOps content to be found anywhere on the Internet—hands down.
In each episode of the podcast (or “Meetup”, as they are labeled by the MLOps.community team) host Demetrios Brinkmann interviews guests who are currently working on exciting machine learning projects in production. As the podcast’s website puts it, the MLOps Community is filling the fast-growing need to share real-world MLOps best practices from engineers working in the field.
AI in Business is led by the founder of artificial intelligence market research company Emerj, Daniel Faggella. This podcast is all about keeping its listeners in tune with how machine learning and AI are transforming industries, and the episodes cover the emerging and critical trends that are shaping how ML is applied in businesses. The podcast also looks at the other side of the coin, covering how business leaders and executives are managing innovation and change.
One of the podcast’s taglines is, ‘Don’t be on the wrong end of disruption’—and if you listen to AI in Business, you will be learning directly from the insights of some of the world’s best and brightest AI and machine learning experts.
In 2016 Pieter Abbeel, the host of The Robot Brains Podcast, joined OpenAI. In his role at OpenAI, Abbeel was responsible for publishing several papers on topics including reinforcement learning and unsupervised learning.
In the same year, he also became co-director of the Berkeley Artificial Intelligence Research (BAIR) Lab, and he also founded the Berkeley Open Arms. In 2017, he then went on to become a full-time professor with tenure at UC Berkeley. To say that he is qualified to host his own machine learning podcast, then, would be something of an understatement.
In each episode of his podcast, Abbeel uses his large network of industry contacts to interview some of the foremost researchers and engineers in the ML field. What is especially impressive about Robot Brains is that the podcast focuses heavily on rational AI and robots, and as an expert in the field himself, he always knows exactly what the most important questions are.
Machine Learning Street Talk is led by Dr. Tim Scarfe, Dr. Yannic Kilcher, and Dr. Keith Duggar. Together, the trio does a phenomenal job of thoroughly researching each show and enabling long, insightful two-way conversations between themselves and some of the most innovative and disruptive people who are shaping the machine learning space. Each episode of the podcast teaches its listeners something new through unfiltered technical conversations.
A quick glance at some of the big names that have been featured on the Machine Learning Street Talk podcast will tell you everything that you need to know about what to expect—Jeff Hawkins, Gary Marcus, Francois Chollet, Pedro Domingos, Yoshua Bengio, and Yann LeCun are just a select few from the long list of featured experts.
Eyes on AI is a biweekly podcast that is hosted by journalist and former New York Times executive Craig S. Smith. While he resigned from the Times in 2018, he is retained as a contributor and primarily writes about artificial intelligence. Smith is also a special Government employee for the National Security Commission on Artificial Intelligence.
In each episode, Smith interviews the leaders making a difference in the ML space. His interviews and episodes tend to cover the latest advances in machine learning, putting them into a broader context and considering their global implications.
Listening to podcasts is easily one of the best ways to keep abreast of the latest developments in the fast-paced world of AI and machine learning.
While we have shared some of our favorites with you, this list is far from exhaustive. With thousands of great podcasters out there focusing on machine learning and related fields, you are guaranteed to find something that interests and engages you.