education
Hosted by Elius Etienne · education · EN-US
The world of AI moves fast. This podcast bridges the gap between simple overviews and dense technicality. Whether you are a Data Scientist prepping for interviews, a student navigating the math, a business leader, or just a curious soul, this is your roadmap. We skip the hype to provide a rigorous, practical guide to the "how" and "why" of Machine Learning.Note: In the spirit of the topic, this show uses AI-generated voices and scripts. However, accuracy is our priority: all content is rigorously verified by a human expert with a PhD in Engineering and professional ML experience.
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Contact path
Public web form
Booking probability
17%
Guest openness
Selective
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Signup to Generate a PitchThe world of AI moves fast. This podcast bridges the gap between simple overviews and dense technicality. Whether you are a Data Scientist prepping for interviews, a student navigating the math, a business leader, or just a curious soul, this is your roadmap.
AI-ML Decoded: From Fundamentals to Future is hosted by Elius Etienne. The show has published 15 episodes to date.
Recent episodes include "E14. An Overview of MLOps" (11 January 2026, 9 minutes), "E13. An Overview of Machine Learning Libraries" (11 January 2026, 6 minutes), and "E12. An Overview of Model Training" (11 January 2026, 9 minutes).
AI-ML Decoded: From Fundamentals to Future publishes roughly daily, with episodes averaging 9 minutes across 15 episodes.
Booking probability for AI-ML Decoded: From Fundamentals to Future is 17%, and the host is rated Selective on guests. AI-ML Decoded: From Fundamentals to Future requires a Pod Score of 80 or higher. AI-ML Decoded: From Fundamentals to Future's contact route on record: public web form.
The strongest fits for AI-ML Decoded: From Fundamentals to Future are IT Services & Software Development. AI-ML Decoded: From Fundamentals to Future has an education audience.
Elius Etienne hosts AI-ML Decoded: From Fundamentals to Future, an education podcast with 15 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.
Episode #14
<p>Episode 14: An Overview of MLOps</p><p>In our season finale, we answer the most practical question of all: What happens after the model is trained? We explore MLOps—the critical "assembly line" practices that take a...
<p>Episode 13: An Overview of Machine Learning Libraries</p><p>Developers don't build AI from scratch. In this episode, we open the toolbox to explore the essential Machine Learning Libraries and frameworks that power...
Episode #12
<p>Episode 12: An Overview of Model Training</p><p>We've used the word "training" in every episode. Now, we break down exactly what it means. In this episode, we explore the step-by-step workflow of how a model actually...
Episode #11
<p>Episode 11: An Overview of Generative AI</p><p>It’s the topic everyone is talking about. In this episode, we broaden our scope from NLP to the entire field of Generative AI—the technology that creates original text...
<p>Episode 10: An Overview of Natural Language Processing</p><p>If Computer Vision allows machines to "see," Natural Language Processing (NLP) allows them to "understand." In this episode, we explore the science behind...
Episode #9
<p>Episode 9: An Overview of Computer Vision</p><p>If Deep Learning is the engine, Computer Vision is the eyes. In this episode, we explore how machines process, analyze, and "see" the world around them—from detecting...
Episode #8
<p>Episode 8: An Overview of Deep Learning</p><p>In almost every episode so far, we've mentioned "Neural Networks." Now, we finally pull back the curtain to explain the engine behind modern AI. In this episode, we...
<p>Episode 7: An Overview of Reinforcement Learning</p><p>So far, we have discussed models that learn from static datasets. Now, we enter the dynamic world of Reinforcement Learning (RL), where "agents" learn to master...
<p>Episode 6: An Overview of Self-Supervised Learning</p><p>We have explored learning with labels and learning without them. Now, we examine the "magic" trick of modern AI: Self-Supervised Learning (SSL), where the...
<p>Episode 5: An Overview of Semi-Supervised Learning</p><p>What do you do when you have a mountain of data, but only a handful of labels? In this episode, we explore Semi-Supervised Learning, the hybrid approach that...
<p>Episode 4: An Overview of Unsupervised Learning</p><p>What happens when you don't have an "answer key"? In this episode, we explore Unsupervised Learning, the branch of AI tasked with finding hidden patterns and...
Episode #3
<p>Episode 3: An Overview of Supervised Learning</p><p>Now that we understand "features," how do models actually learn from them? In this episode, we break down Supervised Learning—the most common approach in modern AI...
Episode #2
<p>Episode 2: An Overview of Feature Engineering</p><p>Before a model can "learn" anything, the raw data must be translated into a language it understands. In this episode, we explore Feature Engineering—the critical...
Episode #1
<p>Episode 1: An Overview of Machine Learning</p><p>In our series premiere, we start at the top with a high-level map of the Machine Learning landscape. Mark and Rachel break down the buzzwords to explain exactly how...
AI-ML Decoded: From Fundamentals to Future
<p>Welcome to AI-ML Decoded: Your Guide to Artificial Intelligence and Machine Learning.</p><p>The world of AI is transforming society in real-time, but keeping up with the technical details can feel overwhelming. In...
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