Are you wanting to learn more about machine learning ? Well you’ve come to the right place. This is a curated list of the best machine learning podcasts of 2021.
We have selected these podcasts for a variety of reasons, but they are all well worth a listen. We tried to select a variety of podcasts across the spectrum from hosts with a wide breadth of experience.
We are always keen to hear your feedback, if we have missed a podcast, tweet us @MagazineWelp and we will check it out!
Best Machine Learning Podcasts 2021
Machine Learning Guide
- Publisher: OCDevel
- Total Episodes: 30
Machine learning audio course, teaching the fundamentals of machine learning and artificial intelligence. It covers intuition, models (shallow and deep), math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-curated resources for each episode’s details at ocdevel.com. Audio is a great supplement during exercise, commute, chores, etc.
Machine Learning – Software Engineering Daily
- Publisher: Machine Learning – Software Engineering Daily
- Total Episodes: 142
Machine learning and data science episodes of Software Engineering Daily.
- Publisher: David Nishimoto
- Total Episodes: 392
Machine learning is the most important technological breakthrough in the 21st century. Listen to my views on the future of machine learning
Practical AI: The Capacity for Good
- Publisher: Changelog Media
- Total Episodes: 133
Practical AI: The Capacity for Good, is a podcast that explores the positive side of artificial intelligence. We speak with thought leaders about the intersection of AI automation, customer support, and customer experience. We dive into real-life stories of how AI has improved people’s lives. Join us as we explore the many ways in which AI can be a force for good and hear from those who are using it to make a positive impact on the world.
Practical AI: Machine Learning & Data Science
- Publisher: Changelog Media
- Total Episodes: 133
Making artificial intelligence practical, productive, and accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, etc). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
Machine Learning Street Talk
- Publisher: Machine Learning Street Talk
- Total Episodes: 53
This is the audio podcast for the ML Street Talk YouTube channel at https://www.youtube.com/c/MachineLearningStreetTalk Thanks for checking us out! We think that scientists and engineers are the heroes of our generation. Each week we have a hard-hitting discussion with the leading thinkers in the AI space. Street Talk is unabashedly technical and non-commercial, so you will hear no annoying pitches. Corporate- and MBA-speak is banned on street talk, “data product”, “digital transformation” are banned, we promise 🙂 Dr. Tim Scarfe, Dr. Yannic Kilcher and Dr. Keith Duggar.
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
- Publisher: Sam Charrington
- Total Episodes: 498
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
Machine Learning Podcast – Jay Shah
- Publisher: Jay Shah
- Total Episodes: 41
Talks with young engineers working in Machine Learning and AI research on how to get started and breakthrough it.
Gradient Dissent – A Machine Learning Podcast by W&B
- Publisher: Lukas Biewald
- Total Episodes: 40
Brought to you by the folks at Weights & Biases, Gradient Dissent is a weekly machine learning podcast that takes you behind-the-scenes to learn how industry leaders are putting deep learning models in production at Facebook, Google, Lyft, OpenAI, Salesforce, iRobot, Stanford and more.
Machine Learning Cafe
- Publisher: Miklos Zoltan Toth
- Total Episodes: 16
This is a machine-learning-focused Podcast, where we interview people in the field of Artificial Intelligence and discuss interesting technical topics of Machine Learning. In the episodes, we focus on business-related use-cases (especially with Deep Learning ) and we also try to bring some technical white papers to the ground, not forgetting on the way that there are always some people behind the technology, so we try to understand their motivation and drive.
MaML – Medicine & Machine Learning Podcast
- Publisher: MAML Pod
- Total Episodes: 8
The Medicine and Machine Learning (MaML) Podcast is run by medical students and graduate students passionate about the burgeoning frontier of healthcare and AI. Each month, we will feature interviews with a prominent figure in industry, academia, or medicine. This podcast is designed for anyone with a budding interest in the field. No coding or medical experience required! Contact: [email protected]
A4N (AI/Machine Learning News)
- Publisher: Jon Krohn
- Total Episodes: 4
A4N — the Artificial Neural Network News Network — is a lighthearted podcast covering the latest developments in artificial intelligence, machine learning, and data science, in which we both introduce technical aspects of these advances, as well as their social implications. The intended audience is anyone interested in automation, A.I., or the future, with brief sections catering especially to professionals working in the fields of data science or software engineering.
Machine Learning for the Masses
- Publisher: NNData
- Total Episodes: 6
Podcast by NNData
Data Futurology – Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science
- Publisher: Felipe Flores
- Total Episodes: 171
Artificial intelligence is a tremendously beneficial technology that’s advancing at an incredibly rapid pace. As more and more organisations adopt and implement AI we find that the main challenges are not in the technology itself but in the human side, ie: the approaches, chosen problems and what’s called ‘the last mile’, etc. That’s why Data Futurology focuses on the leadership side of AI and how to get the most value from it. Join me, Felipe Flores, a Data Science executive with almost 20 years of experience in the space. Every week I speak with top industry leaders from around the world
Learning Machines 101
- Publisher: Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.
- Total Episodes: 83
Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions that will be addressed in this podcast series!
Adventures in Machine Learning
- Publisher: DevChat.tv
- Total Episodes: 44
Seasoned pro or complete beginner, everyone can join our weekly Adventures in Machine Learning podcast. We’re covering all the breakthroughs, influencers, and resources of Machine Learning with our venturesome AI panel and guests. We discuss advanced concepts in plain English. This is the AI podcast you’ve been looking for.
RARE PERSPECTIVES: The AI and Machine Learning Podcast
- Publisher: Radim Řehůřek PhD, creator of Gensim, founder at rare-technologies.com
- Total Episodes: 4
Educated ramblings on AI & machine learning in life and business.
- Publisher: Dr.Priya Pillai
- Total Episodes: 1
A course at Coursera Join for Free from HSNCB
Human-Centered Machine Learning
- Publisher: Halmstad University
- Total Episodes: 13
In this course we will explore the challenges presented when designing AI-powered services. In particular, we will take a look at Machine Learning (such as deep learning and generative adversarial networks), and how that can be used in human-centered design of digital services. This course is created for User Experience (UX) professionals, Service Designers, and Product Managers as a way to help take a human-centered approach to AI in their work. The course is also useful for developers and engineers who want to both learn more about different Machine Learning techniques, and at the same time get a deeper understanding of the importance of a human-centered approach to digital design. The podcast is developed by Pontus Wärnestål, Stefan Byttner, Cristofer Englund and Jeanette Sjöberg at Halmstad University in Sweden, and is financed by VINNOVA. Music by Lee Rosevere. Read more: dap.hh.se
Machine Learning with Coffee
- Publisher: Gustavo Lujan
- Total Episodes: 20
Machine Learning with Coffee is a podcast where we are going to be sharing ideas about Machine Learning and related areas such as: artificial intelligence, business intelligence, business analytics, data mining and Big data. The objective is to promote a healthy discussion on the current state of this fascinating world of Machine Learning. We will be sharing our experience, sharing tricks, talking about latest developments and interviewing experts, all these on a very laid back, friendly manner. So, what are you waiting for? Grab a coffee and join us.
Machine Learning Engineered
- Publisher: Charlie You
- Total Episodes: 32
This podcast helps Machine Learning Engineers become the best at what they do. Join host Charlie You every week as he talks to the brightest minds in data science, artificial intelligence, and software engineering to discover how they bring cutting edge research out of the lab and into products that people love. You’ll learn the skills, tools, and best practices you can use to build better ML systems and accelerate your career in this flourishing new field.