RSS Amplifier

Topic · deep learning

deep learning

The 50 most recent episodes and tracks on this topic.

Saves to your Watch and Listen queue, to pick up on another day or another device.

Pick anything below and it plays in the bar at the foot of the window — and keeps playing while you go on browsing the directory.

  1. But what is cross-entropy? | Compression is Intelligence Part 2Neural networksNotes
  2. Inside Instacart's AI-Powered Smart Shopping Cart | NVIDIA AI Podcast Ep. 302NVIDIA AI Podcast39:55
  3. How Mistral Is Building Frontier AI for the Enterprise | NVIDIA AI Podcast Ep. 301NVIDIA AI Podcast21:33
  4. Everyone Can Build a Robot: Open Source Embodied AI With Seeed Studio | NVIDIA AI Podcast Ep. 300NVIDIA AI Podcast29:04
  5. MIT 6.S191: Secrets of Massively Parallel TrainingMIT 6.S191: Introduction to Deep LearningNotes
  6. Inside AI Tokenomics: How to Profitably Turn Tokens Into Business Value | NVIDIA AI Podcast Ep. 299NVIDIA AI Podcast33:25
  7. MIT 6.S191: AI for ScienceMIT 6.S191: Introduction to Deep LearningNotes
  8. Snap’s Secret to Processing 10 Petabytes a Day: GPU-Accelerated Spark | NVIDIA AI Podcast Ep. 298NVIDIA AI Podcast23:35
  9. MIT 6.S191: The Three Laws of AIMIT 6.S191: Introduction to Deep LearningNotes
  10. Harrison Chase of LangChain on Deep Agents, LangSmith, and Earning Trust | NVIDIA AI Podcast Ep. 297NVIDIA AI Podcast24:54
  11. MIT 6.S191: Language Models and New FrontiersMIT 6.S191: Introduction to Deep LearningNotes
  12. How Dassault Systèmes Is Building AI That Understands Physics - Ep. 296NVIDIA AI Podcast23:04
  13. MIT 6.S191: Reinforcement LearningMIT 6.S191: Introduction to Deep LearningNotes
  14. One Brain, Any Robot: Skild AI's Skild Brain Explained - Ep. 295NVIDIA AI Podcast29:47
  15. MIT 6.S191: Deep Generative ModelingMIT 6.S191: Introduction to Deep LearningNotes
  16. How AI Will Change Quantum Computing - Ep. 294NVIDIA AI Podcast31:28
  17. MIT 6.S191: Convolutional Neural NetworksMIT 6.S191: Introduction to Deep LearningNotes
  18. MIT 6.S191: Recurrent Neural Networks, Transformers, and AttentionMIT 6.S191: Introduction to Deep LearningNotes
  19. MIT Introduction to Deep Learning | 6.S191MIT 6.S191: Introduction to Deep LearningNotes
  20. Building AI Factories: How Red Hat and NVIDIA Turn Enterprise Data Into Intelligence - Ep. 293NVIDIA AI Podcast38:43
  21. Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 1: IntroductionStanford CS231N Deep Learning for Computer Vision I 2025Notes
  22. Stanford CS231N | Spring 2025 | Lecture 2: Image Classification with Linear ClassifiersStanford CS231N Deep Learning for Computer Vision I 2025Notes
  23. Stanford CS231N | Spring 2025 | Lecture 3: Regularization and OptimizationStanford CS231N Deep Learning for Computer Vision I 2025Notes
  24. Stanford CS231N | Spring 2025 | Lecture 4: Neural Networks and BackpropagationStanford CS231N Deep Learning for Computer Vision I 2025Notes
  25. Stanford CS231N | Spring 2025 | Lecture 5: Image Classification with CNNsStanford CS231N Deep Learning for Computer Vision I 2025Notes
  26. Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 6: CNN ArchitecturesStanford CS231N Deep Learning for Computer Vision I 2025Notes
  27. Stanford CS231N | Spring 2025 | Lecture 7: Recurrent Neural NetworksStanford CS231N Deep Learning for Computer Vision I 2025Notes
  28. Stanford CS231N | Spring 2025 | Lecture 8: Attention and TransformersStanford CS231N Deep Learning for Computer Vision I 2025Notes
  29. Stanford CS231N | Spring 2025 | Lecture 9: Object Detection, Image Segmentation, VisualizingStanford CS231N Deep Learning for Computer Vision I 2025Notes
  30. Stanford CS231N | Spring 2025 | Lecture 11: Large Scale Distributed TrainingStanford CS231N Deep Learning for Computer Vision I 2025Notes
  31. Stanford CS231N | Spring 2025 | Lecture 12: Self-Supervised LearningStanford CS231N Deep Learning for Computer Vision I 2025Notes
  32. Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 13: Generative Models 1Stanford CS231N Deep Learning for Computer Vision I 2025Notes
  33. Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 14: Generative Models 2Stanford CS231N Deep Learning for Computer Vision I 2025Notes
  34. Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 15: 3D VisionStanford CS231N Deep Learning for Computer Vision I 2025Notes
  35. Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 10: Video UnderstandingStanford CS231N Deep Learning for Computer Vision I 2025Notes
  36. But how do AI images and videos actually work? | Guest video by Welch LabsNeural networksNotes
  37. MIT 6.S191 (2025): Language Models and New FrontiersMIT 6.S191: Introduction to Deep LearningNotes
  38. MIT 6.S191 (2025): Reinforcement LearningMIT 6.S191: Introduction to Deep LearningNotes
  39. MIT 6.S191 (2025): Deep Generative ModelingMIT 6.S191: Introduction to Deep LearningNotes
  40. MIT 6.S191 (2025): Convolutional Neural NetworksMIT 6.S191: Introduction to Deep LearningNotes
  41. MIT 6.S191 (2025): Recurrent Neural Networks, Transformers, and AttentionMIT 6.S191: Introduction to Deep LearningNotes
  42. Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 14 - Reasoning and Agents by Shikhar MurtyStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  43. Stanford CS224N: NLP w/ DL| Spring 2024 | Lecture 13 - Brain-Computer Interfaces, Chaofei FanStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  44. Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 12 - Efficient Training, Shikhar MurtyStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  45. Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 11 - Benchmarking by Yann DuboisStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  46. Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 10 - Post-training by Archit SharmaStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  47. Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 7 - Attention, Final Projects and LLM IntroStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  48. Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 6 - Sequence to Sequence ModelsStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  49. Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 5 - Recurrent Neural NetworksStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
  50. Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 4 - Dependency ParsingStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes