A collection of the best data science podcast to listen to
I have dabbled in podcasts over the years, but since last year I’ve had a long commute on the New York Subway, and I wanted to find a way to pass the time and still be productive. I started listening to podcasts focusing on Data Science. I was given a lot of recommendations on the best podcasts to listen to, but I found that I gravitated towards a few.
My goal was to understand machine learning and data science, keep up to date with the latest trends and research in data science, understand how data science is applied industry, and understand the overall business strategy. The combination of these different podcasts allowed me to best accomplish my goal.
Katie and Ben co-host Linear Digression, there are over 250 episodes focused on machine learning, statistics, Data Science, and more. Katie serves as the expert explaining technical topics to Ben, who knows very little about the subject. Katie does a great job at breaking down technical topics to a non-technical audience in 30 min or less. What I also like about the podcast is that they introduce content that I never thought about looking into, but turns out to be valuable. Linear Digression is one of the few podcasts that I often go back and listen to previous episodes.
The last episode focused on a research paper published by Google to estimate the long term effect for short term experiments. Focus on the Long-Term: It’s better for Users and Business. Experiments are built to optimize for the short term, but long term consequences are not often apparent.
The previous episode focused on examining the Machine Learning with Statistical Imputation for Predicting Drug Approvals paper with the author, Andrew Lo. The episode documents the process of achieving predictive power in their algorithm, which attracted the attention of industry professionals in the healthcare industry.
Data Skeptic is hosted by Kyle Polich, and is one of the longest-running podcasts in Data Science. There are over 200 episodes focused on interviewing machine learning practitioners and experts. Kyle invites a diverse selection of guest, and excellent at conducting interviews, and
Data strikes the right balance being valuable to both beginners and seasoned professionals: Kyle provides the intuition behind data science and covers the latest tools, methods, and trends.
In 2019 Data Skeptic focused on Natural Language processing, covering topics like BERT, GLUE, ELMO, serverless NLP training, and, more recently, the limits of NLP where Kyle Interview the Google Brain researcher Colin Raffel.
Kyle also does a mini-series with his wife, where he tries to explain a topic to his non-technical wife. The dynamic between them makes a great learning experience.
Data framed is hosted by Hugo Brown Anderson, Data Scientist at Datacamp. The purpose of this podcast is to understand how industries are using data science. Hugo Interviews a variety of guests from different backgrounds and sectors and explores the modern data science landscape, and explore what problem can data science solve and demystifies what it looks like in practice. I found that this podcast bridges the gap between expectation and reality.
Hugo has since stopped publishing new episodes since April 2019, but there are over 50 episodes that are still worth listening to. Some of the people he’s interviewed are Wes Mckinney, Creator of Pandas, Taras Gorishnyy Senior Manager at Mckinsey, Omoju Miller Machine Learning Engineer at Github, and covers industry such as Healthcare, Telecommunications, Finance, Insurance, etc.
Reid Hoffman, the co-founder of LinkedIn and investor at Greylock, shows how companies grow from zero to a gazillion.
Many data scientists are overly optimizing for their technical skills, but the best data science focuses on understanding the business strategy behind data science and the implication of their work as well as the technicals. Whether you are working at a startup or working for Fortune 500 companies, the lessons that you can learn from listening to podcasts are transferable.
My focus has been tackling data science from multiple angles. Together these 4 podcasts provide me with a broad overview of data science.