Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning
Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.
Listening to podcasts during your daily commute or while taking a break from the bustle of your day is an efficient and effective way to stay current on the field of data science and make sure you are always learning more.
The following KDnuggets Top 10 list highlights the most active and popular podcasts so far in 2019 that feature data science and machine learning conversations. We reviewed many more podcasts, so this list drills down to only those published on iTunes with the highest ratings (4.5+), the most reviews, and at least one recent episode within the current month. All show descriptions are adapted from the podcast listing.
We also share a few new and notable podcasts that are either too fresh for competing with the big list, haven’t published in a while but are still an excellent resource, or cover broader topics. You should still consider checking out these shows as they might bring you just the tidbit of knowledge that will lead you to your next big data adventure!
Let us know what you think about our selections and please share your favorite podcasts you believe should be considered in a future best-of list.
The Top 10 in Podcasts
Features interviews and discussion of topics related to data science, statistics, machine learning, and artificial intelligence from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
Latest episode: (20 min.) An interview with Prasanth Pulavarthi about the Onyx format for deep neural networks.
Discussions on the latest developments in data analytics, visualization, and related topics.
Latest episode: (42 min.) Evan Peck is a guest on the show to talk about the research he and his students recently published on "Data Is Personal." The study consists of 42 interviews made in rural Pennsylvania to see how people from different educational backgrounds ranked a set of various data visualizations.
Conversations at MIT and beyond about the nature of intelligence and AI from the perspectives of deep learning, robotics, AGI, neuroscience, philosophy, psychology, cognitive science, economics, physics, and mathematics.
Latest episode: (44 min.) Chris Urmson was the CTO of the Google Self-Driving Car team, a key engineer and leader behind the Carnegie Mellon autonomous vehicle entries in the DARPA grand challenges and the winner of the DARPA urban challenge. Today, he is the CEO of Aurora Innovation, an autonomous vehicle software company he started with Sterling Anderson, who was the former director of Tesla Autopilot, and Drew Bagnell, Uber’s former autonomy and perception lead.
An exploration of machine learning and data science through interesting (and often very unusual) applications.
Latest episode: (16 min.) If you’re Google or Netflix, and you have a recommendation or search system as part of your bread and butter, what’s the best way to test improvements to your algorithm? A/B testing is the canonical answer for testing how users respond to software changes, but it gets tricky fast to think about what an A/B test means in the context of an algorithm that returns a ranked list. That’s why we’re talking about interleaving this week—it’s a simple modification to A/B testing that makes it much easier to race two algorithms against each other and find the winner, and it allows you to do it with much less data than a traditional A/B test.
This Week in Machine Learning & AI caters to a highly targeted audience of machine learning and AI enthusiasts. Covering technologies such as machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, and deep learning.
Latest episode: (75 min.) Zachary Lipton, Assistant Professor in the Tepper School of Business, is the guest whose research is focused on machine learning in healthcare to assist physicians through the diagnosis and treatment process. We discuss supervised learning in the medical field, robustness under distribution shifts, ethics in machine learning systems across industries, and the concept of ‘fairwashing.’
Bringing you the most inspiring Data Scientists and Analysts from around the world to help you build your successful career in Data Science. Data is growing exponentially and so are salaries of those who work in analytics. This podcast can help you learn how to skyrocket your analytics career.
Latest episode: (66 min.) A chat with the Founder and Director of Digital Strategy at Webfor, Kevin Getch. You will learn what digital assistants are and where they're going with the help of people like Ray Kurzweil at Google. You will hear Kevin's philosophy on 'what gets measured gets managed' and what it means for marketing and data science. You will also learn why websites are less and less important, how segmentation is slowly transitioning to personalization, creating amazing customer experiences, disk profiles, natural language processing, and computer vision and their role in the future of marketing.
Katherine Gorman and Neil Lawrence bring you clear conversations with experts in the field, insightful discussions of industry news, and useful answers to your questions. Machine learning is changing the questions we can ask of the world around us, here we explore how to ask the best questions and what to do with the answers.
Latest episode: (45 min.) We talk about On, the marginal likelihood and cross-validation, Katherine is still excited about PosterSession.ai, we invent Deep Quaggles, and listen to a conversation with professor Elaine Nsoesie of BU.
We connect with some of the world’s leading AI experts to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor. NVIDIA, the AI computing company, produces this podcast.
Latest episode: (24 min.) Some say style never fades, and now with the help of AI, finding one’s fashion sense is about to get a whole lot easier. Fashion e-commerce startup Stitch Fix is piecing together a seamless balance between AI-powered decision making and human judgment. We spoke with Stitch Fix Chief Algorithms Officer Brad Klingenberg about how the company is using AI to help us all dress better.
Attend any conference, and you will hear people say that the most informative discussions happened in the bar after the show. Read any business magazine, and you will find an article saying something along the lines of "Business Analytics is the hottest job category out there, and there is a significant lack of people, process and best practice." In this case, the conference was eMetrics, the bar was… multiple, and the attendees were Michael Helbling, Tim Wilson, and Jim Cain (Co-host Emeritus). After a few pints and a few hours of discussion about the cutting edge of digital analytics, they realized they might have something to contribute back to the community. This podcast is one of those contributions. Each episode is a closed topic and an open forum - the goal is for listeners to enjoy listening to Michael, Tim, and Moe share their thoughts and experiences and hopefully take away something to try at work the next day.
Latest episode: (45 min.) Have you ever thought it would be a great idea to have a drink or two, grab a microphone, and then air your grievances in a public forum? Well, we did! This episode of the show was recorded in front of a live audience (No laugh tracks! No canned applause!) at the Marketing Analytics Summit (MAS) in Las Vegas. Moe, Michael, and Tim used a “What Grinds Our Gears?” application to discuss a range of challenges and frustrations that analysts face. They (well, Moe and Tim, of course) disagreed on a few of them, but they occasionally even proposed some ways to address the challenges, too.
Learn what's possible - and what's working - with artificial intelligence in the enterprise through interviews with top AI and machine learning-focused executives and researchers in sectors like Pharma, Banking, Retail, and Defense. Discover trends, learn about what's working now, and learn how to adapt and thrive in an era of AI disruption.
Latest episode: (21 min.) When we polled our audience about what they were interested in, the most selected response was "business intelligence." As a follow-up, we asked them what business intelligence meant to them, and their responses boiled down to anything about understanding the data businesses are already collecting. That kind of broad definition gets to the heart of the confusion surrounding the differences between business intelligence and artificial intelligence. The line is starting to get blurry. Our guest this week is Elif Tutuk, Senior Director at Qlik. Tutuk talks about how business intelligence is evolving and how we might define it now that a lot of BI is becoming AI. Tutuk discusses where AI is making its way into business intelligence and what that might enable for businesses.
New & Notable Mentions
- WiDS (Women in Data Science) from Professor Margot Gerritsen, Stanford University | 10 episodes, 2018 – 2019, iTunes
Data science is improving outcomes in a wide range of domains, from healthcare to seismology to human rights and more. Hear from women leaders across the data science profession, as they share their advice, career highlights, and lessons learned along the way.
Latest episode: (33 min.) Meltem Ballan, a data scientist working on Connected Cars at General Motors, explains how data science is transforming the automotive industry.
Interviews with top and rising luminaries in data science, machine learning, and AI on the trends and business use cases that are propelling the field forward.
Latest episode: (63 min.) In June 2019, over 200 data scientists gathered at Viacom HQ in New York to hear key industry players’ takes on what makes an effective data-driven strategy. Q McCallum, Senior Content Adviser at Formulated.by, took a deeper dive into the major topics of concern for data science when he spoke with DSS NYC speakers Lauren Lombardo, Senior Data Scientist at Nielsen and Sergey Fogelson, Vice President of Data Science and Modeling at Viacom. Listen as they speak about current practices and debate how the growth of AI will impact advertising.
Today's Leading Minds Talk AI with Host Byron Reese.
Latest episode: (30 min.) In this episode, Byron speaks with guest Chris Duffey about the nature of creativity and how machine intelligence can interact with creative concepts.
Teaches the high-level fundamentals of machine learning and artificial intelligence including basic intuition, algorithms, and math. With discussions on languages and frameworks and deep learning, each episode offers a high-quality curated resource for learning each episode’s details.
Latest episode: (42 min.) Introduction to reinforcement learning concepts.
Discover the hidden side of everything with Stephen J. Dubner, co-author of the Freakonomics books. Each week, Freakonomics Radio tells you things you always thought you knew (but didn’t) and things you never thought you wanted to know (but do) — from the economics of sleep to how to become great at just about anything. Dubner speaks with Nobel laureates and provocateurs, intellectuals and entrepreneurs, and various other underachievers. Special features include series like “The Secret Life of a C.E.O.” as well as a live game show, “Tell Me Something I Don’t Know.”
Latest episode: (52 min.) We all know our political system is “broken” — but what if that’s not true? Some say the Republicans and Democrats constitute a wildly successful industry that has colluded to kill off competition, stifle reform, and drive the country apart. So, what are you going to do about it?
Covering a wide array of Python and related topics, our goal is to bring you the human story behind the Python packages and frameworks you know and love.
Latest episode: (67 min.) How do we get kids excited about programming? Make programming tangible with embedded devices. Did you know that after kids learned to code with the BBC micro:bit, 90% of kids "thought coding was for everyone," and 86% said it made CS topics more interesting?
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