Podcast Index
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The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations
Fexingo
Shares for Beginners
Philip Muscatello - Australian Investor Education
美股早咖啡
Meng
Your Brain at Work
Neuroleadership Institute
Insurance Exam Prep
Ran Chen, EA, CFP®
Stay On Course: Ingredients for Success
Julie Riga
The Arena! Podcast
Hoody Frankliano
High Voltage Business Builders Podcast
Neil Twa
TBPN
John Coogan & Jordi Hays
Global Economic Press
Global Economic Press
NTD Evening News
NTD Evening News
SECRETOS DE UN EMPRENDEDOR
Streamla
3Bs Radio
3Bs Radio
Work On Your Game: Discipline, Structure, and Execution Under Pressure
Dre Baldwin
Artificial Intelligence Growth Architect | Connor with Honor | Real Estate Consultant
Connor T. MacIvor | Connor with Honor
吳淡如人生實用商學院
吳淡如
美商挖挖Wow
LA小丹丹
Web3 101
Web3 101
The Level Up Podcast w/ Paul Alex
Paul Alex Espinoza
Financial Home Stretch
David Polatis
Pathway To Retirement
Daniel Flores
Bitcoin Liberty Live
Fritz
Valuetainment
Valuetainment Episodes
Achievers Therapy
Kingsley Nwaekwe
LifeBlood
LifeBlood
7 Minute Leadership
Paul Falavolito
InvestTalk
Hosts Justin Klein & Luke Guerrero, CFA | Wealth Managers and Investment Advisors
Joel Bomgar on Bitcoin: The FB Live Audio
Joel Bomgar
Bloomberg Law
Bloomberg
Real Estate Exam Prep
Ran Chen, EA, CFP®
NZZ Akzent
NZZ
Commanding Morning
Peter Adekeye
No Vacancy Live!
No Vacancy Live
Dare To Shine Podcast for Inspiration
Pamela Geer
Ca$hMire de Pierre Couture
Pierre Couture
The Jas Johal Show
CKNW / Curiouscast
Digital Social Hour
Sean Kelly
Business
Fexingo
In this episode, Lucas and Luna dive into the practical applications of Sentence-BERT (SBERT) for semantic search in production. They discuss how SBERT converts text into dense vector embeddings, enabling similarity sear...
Lucas and Luna explore the practical use of SHAP (SHapley Additive exPlanations) for interpreting complex machine learning models. They walk through a real-world example: a credit risk model from a mid-sized European fin...
For Episode 100 of The Data Science Podcast, Lucas and Luna explore the controversial practice of training AI models on synthetic data. With real-world examples from autonomous vehicle companies like Waymo and medical im...
In this episode, Lucas and Luna dive into Temporal Fusion Transformers (TFT), a deep learning architecture that has changed how data scientists approach time series forecasting. They walk through a concrete case from a m...
In this episode, Lucas and Luna dive into how Spotify uses reinforcement learning to personalize playlists like Discover Weekly and Release Radar. They break down the multi-armed bandit problem, explore how Spotify balan...
Episode 97 dives into counterfactual explanations — the 'what if' tools helping data scientists debug models and build stakeholder trust. Lucas and Luna walk through a concrete example: a credit-approval model that rejec...
In this episode, Lucas and Luna dive into multimodal zero-shot learning, the technique that lets AI models like CLIP recognize objects, scenes, and text across images without ever being explicitly trained on those combin...
In Episode 95 of The Data Science Podcast with Fexingo, Lucas and Luna dive into a practical yet underappreciated technique: using k-nearest neighbors for anomaly detection. They kick off with a real-world story from a m...
In episode 94 of The Data Science Podcast with Fexingo, Lucas and Luna explore how active learning cuts labeling costs by 80 percent while maintaining model accuracy. Using a concrete example from a medical imaging start...
Episode 93 of The Data Science Podcast with Fexingo dives into Thompson Sampling, a Bayesian approach to online experimentation that balances exploration and exploitation better than traditional A/B testing. Lucas and Lu...
Episode 92 of The Data Science Podcast with Fexingo dives into embedded analytics—the practice of integrating dashboards, reports, and AI insights directly into customer-facing products. Lucas and Luna explore how compan...
Most marketing attribution models are correlational — they tell you what happened, not why. In this episode, Lucas and Luna break down how data scientists are using causal inference techniques, specifically double machin...
In this episode, Lucas and Luna explore how knowledge graphs are supercharging retrieval-augmented generation (RAG) systems. They break down a concrete example: how a financial services firm used a knowledge graph built ...
Lucas and Luna explore how graph neural networks are transforming recommendation systems, using the example of Pinterest's PinSage model. They break down how GNNs capture relational data like user-item interactions to ge...
Episode 88 of The Data Science Podcast dives into dimensionality reduction — but not for preprocessing. Lucas and Luna explore how data scientists use t-SNE and UMAP to visualize high-dimensional data, from customer segm...
In episode 87 of The Data Science Podcast, Lucas and Luna explore manifold learning—a powerful technique for dimensionality reduction that goes beyond PCA. They focus on t-SNE and UMAP, explaining how these algorithms pr...
In this episode, Lucas and Luna explore the concept of the Pareto frontier, a powerful framework for multi-objective optimization in data science. Starting with a concrete example—a ride-hailing company balancing driver ...
Lucas and Luna dive into Neural Radiance Fields (NeRFs), a technique that has reshaped 3D reconstruction from 2D images. They walk through how NeRFs work at a high level—converting sparse photographs into continuous volu...
In this episode of The Data Science Podcast, Lucas and Luna explore how data scientists are using diffusion models — the technology behind tools like DALL-E and Stable Diffusion — for image generation. They break down th...
In this episode, Lucas and Luna explore how data scientists apply transfer learning to solve image classification problems with very little labeled data. They break down the concrete steps: taking a pre-trained model lik...
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