Description:Data Skeptic is one of the best-known data science podcasts. This weekly show explores topics in data science, statistics, machine learning and artificial intelligence.
Hosted by Kyle Polich, the show is going strong with over 200 episodes for listeners to dive into. Recently, the show has released series of themed episodes that revolve around a larger topic in the data science world, like fake news.
The episodes alternate between interviews with industry professionals and minisodes that explain high-level data science concepts.
The minisodes are co-hosted by Linh Da Tran, who talks with Kyle about data science topics, like natural language processing and k-means clustering. Listeners gain a better understanding of the topic as the hosts talk through it.
Description:Katie Malone and Ben Jaffe host Linear Digressions, a weekly podcast that explores recent developments in data science, machine learning, and artificial intelligence. The hosts are good friends, and their rapport makes each episode very accessible and easy to understand.
As of this writing, there are over 100 episodes for listeners to dive into. Each episode clocks in at around half an hour, making it a breeze to gain a quick understanding of the topic at hand.
Katie and Ben do a great job at distilling a complex technical topic down to its fundamentals. In just a few short minutes, they demystify neural networks, autoencoders, the Fourier transform, and more.
Description: This podcast on data visualization focuses on a very specific subset of the data analysis pipeline—a rare gem among data science podcasts. Data viz specialists Enrico Bertini and Moritz Stefaner sit down with a guest every other week to discuss data analysis and visualization.
The show has quite a conversational tone. The hosts bounce ideas off of one another, ask great questions of their guests, and generally keep the conversation flowing. With around 40 minutes of runtime, listeners can settle in to really learn about how we can better visualize our data, as well as the role that data plays in our everyday lives.
Description:Kirill Eremenko is a data science coach and lifestyle entrepreneur, and he brings his experience as an influencer to the SuperDataScience podcast. In his interview episodes, he talks with data scientists and data analysts to learn more about their career paths and how they were able to succeed in the data industry.
In addition to interviewing industry experts, the host airs minisodes that are purely inspirational! Called Five Minute Friday, these minisodes aim to inspire listeners to improve themselves as data scientists, and to offer advice on how to advance in a data science career. This is definitely one of the most motivational data science podcasts out there!
Description:Former public radio producer Katherine Gorman believes that continuing the public conversation about data science, AI, and machine learning is absolutely essential to preventing another AI winter.
She believes that data science podcasts are a great venue for that discussion. To this end, she hosts Talking Machines along with Professor Neil Lawrence.
The podcast aims to introduce machine learning to a wide audience and help industry professionals, business leaders, and interested laypeople better understand these tools and technologies.
The episodes generally follow a simple format: the hosts chat about industry news, interview a guest, and in the end may answer a listener question. Episodes are released in seasons and tend to be on the longer side at around 40 minutes.
This is where Katherine’s history as a radio host comes in handy: she keeps the show engaging and informative, and works hard to make sure the it presents an accurate picture of the machine learning industry.
Description: Ben Lorica is the Chief Data Scientist at O’Reilly Media. In each episode, he is joined by an industry professional to discuss topics in big data and data science. The episodes run anywhere from 30 to 40 minutes and are very accessible to listen to.
At the beginning of each episode, the host promotes an event series that listeners can attend to learn more about the topics covered in the podcast. The ones mentioned in the intro are the Strata Data Conference and the Artificial Intelligence Conference, but you can find more of the O’Reilly conferences on their event page.
Description: Partially Derivative is a podcast about Data Science in the world around us. Episodes are a mix of explorations into the techniques used in Data Science and discussions with the field's leading experts. The podcast is a personal project hosted by Jonathon, Vidya, and Chris -- three experts in Data Science.Website iTunes