The U.S. Bureau of Labor statistics estimates that 11.5 million new data science jobs will be added by 2026. This projection suggests that the field of data science will continue to rapidly grow with the high demand for these positions in industry. For those just starting out in the space or considering a transition from another industry, podcasts are useful for developing an understanding of data science and machine learning in industry and research. In this post, I will discuss three of my favorite podcasts that discuss the data science field in research and industry. These podcasts also suggest learning resources for those how are just starting out.

It seems like AI, data science, machine learning and bots are some of the most discussed topics in tech today. My preferred way to do this is always through listening to podcasts. Here are the ones I've found the most interesting: They alternate between great interviews with academics & practitioners and short 10–15 minute episodes where the hosts give a short primer on topics like calculating feature importance, k-means clustering, natural language processing and decision trees, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings. Hosted by Katie Malone and Ben Jaffe, this weekly podcast covers diverse topics in data science and machine learning: talking about specific concepts like model theft and the cold start problem and how they apply to real-world problems and datasets.

Data Skeptic takes a different take on how we review data--thanks to some healthy skepticism, listeners come out with unusual information and knowledge. The show alternates between interviews with industry experts, and mini episodes wherein the host explains data science tidbits to his non data scientist wife. The tone of this show is simultaneously intellectual and a bit off beat. It's fun, and easier to follow than highly technical podcasts. If you need a series with nice production quality and clear, friendly radio voices, this may be the one.

Data science and machine learning have long been interests of mine, but now that I'm working on Fuzzy.ai and trying to make AI and machine learning accessible to all developers, I need to keep on top of all the news in both fields. My preferred way to do this is through listening to podcasts. I've listened to a bunch of machine learning and data science podcasts in the last few months, so I thought I'd share my favorites: Every other week, they release a 10–15 minute episode where hosts, Kyle and Linda Polich give a short primer on topics like k-means clustering, natural language processing and decision tree learning, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings. Hosted by Katie Malone and Ben Jaffe of online education startup Udacity, this weekly podcast covers diverse topics in data science and machine learning: teaching specific concepts like Hidden Markov Models and how they apply to real-world problems and datasets.

There are now enough of us interested in this obscure geeky topic that there are podcasts dedicated to chatting about the ins and outs of predictive modeling. There has never been a better time to get started and working in this amazing field. In this post, I want to share the 5 podcasts on machine learning and data science that I listen to. Here's the short list of machine learning podcasts that I currently listen to: I've tried a number of others, but they have fallen out of my listening cycle. This is a high-quality show that includes segments on technique explanation, listener questions and a main interview. The show brings together Katherine Gorman (a story teller) and Ryan Adams (a machine learning academic).

It seems like AI, data science, machine learning and bots are some of the most discussed topics in tech today. My preferred way to do this is always through listening to podcasts. Here are the ones I've found the most interesting: They alternate between great interviews with academics & practitioners and short 10–15 minute episodes where the hosts give a short primer on topics like calculating feature importance, k-means clustering, natural language processing and decision trees, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings. Hosted by Katie Malone and Ben Jaffe, this weekly podcast covers diverse topics in data science and machine learning: talking about specific concepts like model theft and the cold start problem and how they apply to real-world problems and datasets.

It seems like AI, data science, machine learning and bots are some of the most discussed topics in tech today. My preferred way to do this is always through listening to podcasts. Here are the ones I've found the most interesting: They alternate between great interviews with academics & practitioners and short 10–15 minute episodes where the hosts give a short primer on topics like calculating feature importance, k-means clustering, natural language processing and decision trees, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings. Hosted by Katie Malone and Ben Jaffe, this weekly podcast covers diverse topics in data science and machine learning: talking about specific concepts like model theft and the cold start problem and how they apply to real-world problems and datasets.

In order to protect the world's iconic marine wildlife including whales, sea turtles and sharks, we first have to understand their biology. However, this is often easier said than done. In this 45-minute interactive lesson, students will be taken around the world to learn about new and exciting ways that marine scientists are uncovering the lives of these elusive creatures. Track humpback whales as they feed in Alaska, and come along for the ride as video cameras are deployed on sea turtles in Western Australia. The lesson uses photos and videos from a variety of active research projects, begins with historical context about human impacts on marine wildlife populations and ends with a discussion of what students can do in their lives to help learn about and protect our oceans.

This column is by Matt Fogel, Co-Founder, Fuzzy.io Data science and machine learning have long been interests of mine, but now that I'm working on Fuzzy.ai I need to keep on top of all the news in both fields. My preferred way to do this is through listening to podcasts. I've listened to a bunch of machine learning and data science podcasts in the last few months, so I thought I'd share my favorites: Every other week, they release a 10–15 minute episode where hosts, Kyle and Linda Polich give a short primer on topics like k-means clustering, natural language processing and decision tree learning, often using analogies related to their pet parrot, Yoshi.

Data science and machine learning have long been interests of mine, but now that I'm working on Fuzzy.io I need to keep on top of all the news in both fields. My preferred way to do this is through listening to podcasts. I've listened to a bunch of machine learning and data science podcasts in the last few months, so I thought I'd share my favorites: Every other week, they release a 10–15 minute episode where hosts, Kyle and Linda Polich give a short primer on topics like k-means clustering, natural language processing and decision tree learning, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings.