MLOps Blog

Top 12 Machine Learning Podcasts That You Want to Check as a Data Scientist

4 min
5th September, 2023

As we know, education in this digital age is available in many forms like videos, PDFs, e-books, and podcasts. Podcasts have become more popular among students or learners due to easy accessibility with electronic devices and the ability to make a good connection between the listener and speaker.

“The medium of podcasting and the personal nature of it, the relationship you build with your listeners and the relationship they have with you—they could be just sitting there, chuckling and listening…there’s nothing like that.”

– Marc Maron

In this article we are going to cover up top 12 podcasts that you should check out as a data scientist.

1. Machine Learning as a Software engineer


This conversation is with the Co-founder & CEO of paperspace, Dillion Erb. Paperspace provides GPU-enabled compute resources to data scientists and machine learning engineers. Dillion, explains how they build an organization which helps in building and scaling of machine learning workflows.

Host: Sam Charrington

Guest: Dillion Erb

2. NLP on COVID-19 and Mental Health

Source:  Karli Carpenter

The pandemic(COVID-19) is going on and COVID-19 cases have skyrocketed since December 2019. The more the cases the more we will have data about the patients. In this podcast, Johannes Eichstaedt an assistant professor of psychology at Stanford University talking about the use of social media data such as Twitter and Facebook to understand the psychological behavior of a large populations and individuals.

Host: Sam Charrington

Guest: Johannes Eichstaedt

3. Neural Augmentation for Wireless Communication

In this podcast, Max Welling, a research chair in Machine Learning at the University of Amsterdam and a VP of Technologies at Qualcomm proposes a principle called Neural Augmentation.

In Neural Augmentation, we leverage the power of deep learning to learn the patterns that are impossible to detect by simple human observations. So we train a neural network to iteratively correct the classical solutions by using the three principles.

  1. Error Estimation
  2. MIMO demodulation
  3. Channel Estimation

You can learn more about the Neural Augmentation in this PDF.

Host: Sam Charrington

Guest: Max Welling

4. Quantum Machine Learning

quantum machine learning
Source: plotplot

Quantum machine learning is an intersection of Quantum Physics and Machine Learning.

A quantum computer uses qubits. Qubits are added with the ability to be put into superposition and share entanglement with one another.

By leveraging the techniques superposition and entanglement quantum computers can perform quantum operations that are difficult to process with the standard computers.

In this podcast, Iordanis Kerenidis who is a CNRS senior researcher  at the Algorithms and Complexity Group at IRIF, University Paris Diderot explores the possibilities of quantum machine learning.

Host: Sam Charrington

Guest: Iordanis Kerenidis

5. Disrupting DeepFakes

desrupting fake news
Source: Youtube (Sensity)

Deepfake could generate realistic or convincing fake videos of a person saying or doing which may never happened in the real life. You can imagine or maybe not that how much chaos this can create.

In order to prevent malicious users from generating adversarial attacks against such image translation systems, which disrupt the resulting output image. This problem is called as Disrupting Deepfakes.

In this podcast, Nataniel Ruiz who is a second year PhD candidate at Boston University in the Image & Video Computing group discusses the concepts of Disrupting DeepFakes.

Host: Sam Charrington

Guest: Nataniel Ruiz

6. The intersection of AI and Computer Graphics

ai and computer graphics
Source: Nvidia

NVIDIA GPUs and deep learning trained a neural network to produce facial animations directly from the actor videos. It requires only five minutes of training data. The trained network generates all facial animation needed for the entire game from a video.

In this podcast, Aaron Lefohn who is a Senior Director of Real-Time Rendering Research at NVIDIA will talk about the how the power of AI can be harnessed to generate videos of facial animation from the actor videos.

Host: Noah Krevitz

Guest: Aaron Lefohn

7. Neural Networks, Mathematics & Teaching

neural networks
Source: 3Blue1Brown

Grant Sanderson is an educator on YouTube who makes visualization of mathematics which helps in understanding mathematics on a much deeper level.

In this podcast, Grant will give his insights about the collaboration between machine learning and mathematics. Grant will also tell how he was inspired by the teaching style of famous American Physicist Richard Feynman.

Host: Lex Fridman

Guest: Grant Sanderson

8. Getting Waymo into autonomous driving

Source: Waymo

Waymo is an autonomous driving technology development company. It is a subsidiary of Alphabet Inc, the parent company of Google. Waymo operates a commercial self-driving taxi service in Phoenix, Arizona called “Waymo One”.

In this podcast, Drago Anguelov who is a Principal Scientist and Head of Research at Waymo will talk about AI-powered autonomous driving by explaining the hosts about the algorithms for autonomy.



Drago Anguelov

9. Predicting Floods

Source: Google Research

With the help of AI, we can come up with a mathematical model to train with the past rainfall and water level data which can help us in preparing for the crisis to reduce it’s damage to the minimum.

In the following podcast, Sella Nevo who works at Google Research team working on a flood forecasting project. Sella will talk about the inundation model, the real-time water level measurements, elevation map creation, hydraulic modeling.

Hosts: Katheryn Corman & Neil Arms

Guest: Sella Nevo

10. Difference between artificial intelligence and ‘real’ intelligence

Source: BitFinance

Intelligence can be called as mental ability for reasoning, problem solving or learning. Because it relies upon the cognitive functions of our brains. Now in this digital era, we have also coined a term called Artificial Intelligence, which is acquired by training the data with the help of mathematical models.

In this podcast, Andrew Busey an American Entrepreneur talks about the difference between the “real” intelligence and Artificial Intelligence.

Host: Byron Reese

Guest: Andrew Busey

11. A reality check on AI-driven medical assistants

medical assistant
Source: MedCityNews

The biomedical data has helped researchers to build mathematical models to automate the portions of healthcare process. For example, we can use computer vision to detect whether a patient suffering from pneumonia or not by giving input as an X-ray image.

In this podcast, Katie Malone who is a data scientist in the research and development department at Civic Analytics talks about algorithms like computer vision, one that diagnoses diabetic retinopathy, and another that classifies liver cancer.

Host: Ben Jaffe

Guest: Katie Malone

12. Criminology and data science

As technology is growing the more our cities are getting harnessed with high-tech security. This provides cities with sources of real-time information that is happening throughout the day in a city.

For example, if we train a machine learning model on a chain snatcher videos then we can run the inference with the model on the real-time environment to detect whether someone’s chain is being snatched or not.

In this podcast, Zach Drake who is a Ph.D. student in Criminology, Law, and Society who imparts the knowledge on the collaboration of AI and Criminology with the host Katie Malone.

Host: Katie Malone

Guest: Zach Drake

Well after all these podcasts you might have or certainly become somewhat interested in learning Data Science. So I am listing out the resources where you can learn machine learning for free.

Final thoughts

AI is becoming the new oil for many businesses and what we cover was just the tip of the iceberg,so you better harness yourself with the knowledge of the AI spells to make this world a better place.

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