61% matchBest podcasts for Machine Learning & Data Science guests
40 podcasts semantically matched to the Machine Learning & Data Science vocabulary, grouped by how closely their episode topics align and sorted by score within each group, highest first.
Top Machine Learning & Data Science podcasts by Pod Score
40 matchedEvery machine learning & data science-relevant podcast in our index, ranked by Pod Score (audience size, ratings, and host openness combined). Topical-fit tier shown on each card as a secondary signal.
61% match
61% matchThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
64% matchUnsupervised Learning
62% matchMLOps.community
64% matchUnsupervised Learning
62% matchAdventures in Machine Learning
62% matchBrain Inspired
63% matchArtificial Intelligence Exposed
61% matchGradient Dissent: Conversations on AI
61% matchChris's AI Deep Dive
64% matchPlumbers of Data Science
64% matchAI Daily News Podcast
63% matchUnsupervised Learning (Member Edition)
64% matchDataTalk
61% matchDeep Learning with PolyAI
61% matchUnzip
61% matchSciences des données - Stéphane Mallat
61% matchLearning Machines 101
67% matchMachine Learning Masters
63% matchMachine Learning Guide
dsacademybr
61% matchData Science Academy
63% matchEarthly Machine Learning
62% matchMario Filho - Inteligência Artificial e Machine Learning
62% matchIntroduction to Machine Learning
62% matchPipeline Conversations
61% matchMastering Language Models: From Architecture to Optimization
61% matchData Science Decoded
63% matchMachine Learning Engineered
62% matchMachine Learning Guide
62% matchBuilding functional AI applications
62% match“The Neural Journey” – An exploration of AI concepts for the curious
63% matchflashingpulse
62% matchAI-ML Decoded: From Fundamentals to Future
62% matchNatural Language Generation
62% matchDr. Robert Krug
65% matchMachine Learning for Physicists
62% matchDeep Dive into Networked AI
62% matchThe Machine Learning Debrief
63% matchAdvanced Machine Learning
Topics regularly covered in Machine Learning & Data Science Podcasts
These are the sub-areas, terminology, and adjacent concepts that machine learning & data science podcasts return to most often. Use them as pitch hooks: name the specific topic, not the umbrella term.
- Machine
- learning
- deep
- neural
- networks
- natural
- language
- processing
- computer
- vision
- reinforcement
- supervised
- unsupervised
- feature
- engineering
- model
- training
- overfitting
- regularization
- gradient
Read the full Machine Learning & Data Science podcast field overview
Machine learning, deep learning, neural networks, natural language processing, computer vision, reinforcement learning, supervised learning, unsupervised learning, feature engineering, model training, overfitting, regularization, gradient descent, backpropagation, TensorFlow, PyTorch, scikit-learn, Kubernetes, data pipelines, ETL, SQL, Python, R, big data, Hadoop, Spark, analytics, business intelligence, data visualization, statistics, probability, algorithms, data engineering, MLOps, model deployment, AI ethics, bias detection, data privacy, GDPR, data science careers.
Latest Machine Learning & Data Science episodes
Recent episodes from the top 8 podcasts matched to Machine Learning & Data Science. Reference one of these in your pitch; hosts notice when you've actually listened.
5mMost Companies Aren't Anywhere Near Ready for AI
5mMost Companies Aren't Anywhere Near Ready for AI
32mWe're All Building a Single Digital Assistant
32mWe're All Building a Single Digital Assistant
1h 16mWhy AI Will Replace Knowledge Workers
1h 16mWhy AI Will Replace Knowledge Workers
42mMLA 030 AI Job Displacement & ML Careers
51mMLA 029 OpenClaw
37mMLA 028 AI Agents
See all latest Machine Learning & Data Science episodes
Frequently asked questions
Which podcasts should a Machine Learning & Data Science founder pitch first?
Start with Machine Learning Masters, Machine Learning for Physicists, AI Daily News Podcast; these scored the strongest semantic alignment to Machine Learning & Data Science in our analysis.
How does PitchCentric decide which podcasts are about Machine Learning & Data Science?
We don't rely on Apple Podcasts categories. those are too coarse. Instead, we generate a detailed vocabulary description of Machine Learning & Data Science, embed it as a high-dimensional semantic vector, then compare to similarly-embedded vectors for every podcast in our catalog. The shows that score highest on cosine similarity are the ones whose actual episode content most aligns with Machine Learning & Data Science.
What does a "Strong match" actually mean?
A Strong match (cosine similarity ≥ 0.60) means the podcast's episode topics overlap substantially with the Machine Learning & Data Science vocabulary. Hosts on these shows discuss Machine Learning & Data Science topics every few episodes; a guest pitch with a specific Machine Learning & Data Science angle should fit naturally. Moderate (0.45–0.60) is adjacent; light (0.30–0.45) is crossover.
How often do you re-rank Machine Learning & Data Science podcasts?
Every podcast's embedding refreshes when its description, topic list, or new episodes change. typically every 24-48 hours. So this page reflects the current state of the catalog.
Can I pitch all 40 podcasts at once?
Yes. PitchCentric generates a unique, episode-aware pitch for each show automatically. referencing recent episodes, host interests, and your background. Pitches send from your real Gmail or Outlook inbox so replies land where they should. Free 15-day trial.
Pitch every show on this page with one AI-personalised email
PitchCentric generates a unique, episode-aware pitch for each show, sends it from your real inbox via Gmail or Outlook, and tracks replies in one workspace. 15-day free trial.
