Although the term 'machine learning' was coined almost sixty years ago, it’s only in the past few years that this field of computer science has become a hot topic in the programming community. While most basic programming revolves around creating explicit instructions for machines to follow, machine learning methods enable programs to use models and sample inputs to create their own patterns to allow them to make predictions.
Essentially, machine learning creates smarter programs that help devices and applications ‘teach’ themselves.
While most of us interact with ML-based programs everyday, such as virtual personal assistants like Siri, and recommendation engines in streaming services and social networks, few people know the details behind what makes these features possible.
Whether you already work with data models and artificial intelligences, want to transition into this field, or simply want to know more about what ML is and how it can be applied, we’ve curated a list of 10 excellent podcasts that’ll help keep you up to date on this growing field.
You might also like: Top 10 Podcasts for App Developers.
![machine learning podcast: machine learning guide](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-machine-learning-guide.png?v=1524063670)
This series is hosted by Tyler Renelle, a web and mobile developer transitioning into the field of machine learning. Machine Learning Guide is aimed at covering the basics of ML and artificial intelligence, and is suited for people who are curious about this field but haven’t yet taken the leap into any courses on the data science of machine learning.
![machine learning podcast: data skeptic](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-data-skeptic.png?v=1524063707)
Data and statistical models provide the backbone and fuel for machine learning models. However, is the data were using—and the way we’re using it—truly useful? In Data Skeptic, host Kyle Polich explores this question by alternating between long-form interviews with experts in the field, and mini-episodes that offer a high level overview of some aspects of the data science used in ML.
![machine learning podcast: this week in ml and ai](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-this-week-in-ml-and-ai.png?v=1524063726)
If you want to stay on top of the biggest trends and newest developments in ML and AI, this is podcast you’ll want to follow. Each week on This Week in Machine Learning and AI, hosts Sam Charrington interviews some of the top researchers in the field to discuss the ever increasing uses of machine learning and artificial intelligence.
![machine learning podcast: oreilly](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-oreilly.png?v=1524063833)
This podcast is excellent for anyone wanting to dive deeper into the data science behind machine learning, and the techniques and analysis used to drive AI. The episodes of O’Reilly Data Show are around half an hour each, and are packed with information.
![machine learning podcast: talking machines](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-talking-machines.png?v=1524063854)
With their backgrounds in radio production and academic computer science, co-hosts Katherine Gorman and Neil Lawrence provide a glimpse into the world of machine learning that’s both thorough and accessible to all knowledge levels. Each week’s episode of Talking Machines looks at how machine learning is changing the world around us, and how we can make the best use of these changes.
![machine learning podcast: data framed](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-data-framed.png?v=1524063871)
The field of data science is growing quickly, and is considered to be one of the hottest jobs of the 21st century. But what exactly does working in data science look like? In Data Framed, host Hugo Bowne-Anderson dives into why data science had become so popular and what problems it’s aiming to solve.
![machine learning podcast: linear digressions](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-linear-digressions.png?v=1524063889)
Although this discipline is based around making smart predictions, many applications of machine learning have been far from predictable. Linear Digressions, hosted by data scientist Katie Malone and user interface engineer Ben Jaffe, often explores the more unusual applications of machine learning.
![machine learning podcast: concerning ai](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-concerning-ai.png?v=1524063910)
As the prevalence of artificial intelligence in our society increases, so do the ethical questions around it. If you’re concerned if AI is using the data we provide it responsibly, or you watched Terminator too much as a child and fear the robot uprising, you’ll appreciate the existential questions raised in the Concerning AI podcast.
![machine learning podcast: data stories](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-data-stories.png?v=1524063942)
Despite having launched in early 2012, Data Stories hosts Enrico Bertini and Moritz Stefaner are still serving up fresh and interesting data-based content. These hosts and their guests are so passionate about the subject that despite the often visual nature of the data models they discuss, their enthusiasm and detailed descriptions really help bring the numbers and models to life.
![machine learning podcast: learning machines](http://cdn.shopify.com/s/files/1/0533/2089/files/machine-learning-podcast-learning_machines.png?v=1524063972)
Interacting with AI has become an everyday part of life, and you may want to know more about these intelligent machines and how effective (or ineffective) they actually are. Learning Machines 101 covers how machines actually implement machine learning, and clarifies facts and myths around how smart machines actually work.
Is there a particular series you enjoy that’s not mentioned on this list? Let us know in the comments below!