:Search:

Oreilly Distributed Machine Learning Patterns Video Edition FreeCourseWeb

Torrent:
Magnet Download .torrent File
Info Hash: 1581E53F329C9DBAF6283E6BE36D42995E54AAB9
Similar Posts:
Name Uploaded Size Se Le Upl. by
Oreilly Distributed Machine Learning Patterns Video Edition FreeCours… Oreilly Distributed Machine Learning Patterns Video Edition FreeCourseWeb
2024-03-21 941.8 MB 3 0 FreeCourseWeb
[ FreeCourseWeb ] Oreilly - Distributed Database (DDBMS) Complete Gui… [ FreeCourseWeb ] Oreilly - Distributed Database (DDBMS) Complete Guide
2023-06-02 488.4 MB 0 4 freecoursewb
TutGee Oreilly Get started with Distributed Tracing TutGee Oreilly Get started with Distributed Tracing
2023-10-26 292.7 MB 0 3 freecoursewb
Uploader: FreeCourseWeb
Source: T Logo Torrent Galaxy
Downloads: 149
Language: English
Category: Other
Size: 941.8 MB
Added: March 21, 2024, 5:46 p.m.
Peers: Seeders: 3, Leechers: 0 (Last updated: 10 months, 4 weeks ago)
Tracker Data:
Tracker Seeders Leechers Completed
udp://tracker.opentrackr.org:1337/announce 1 0 62
udp://tracker.openbittorrent.com:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.internetwarriors.net:1337/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.leechers-paradise.org:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.coppersurfer.tk:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://exodus.desync.com:6969/announce 0 0 2
udp://tracker.rarbg.torrentbay.st:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.tiny-vps.com:6969/announce 1 0 5
udp://open.demonii.si:1337/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.torrent.eu.org:451/announce 1 0 80
Files:
  1. Get Bonus Downloads Here.url 183 bytes
  2. 001. Part 1. Basic concepts and background.mp4 2.4 MB
  3. 002. Chapter 1. Introduction to distributed machine learning systems.mp4 27.9 MB
  4. 003. Chapter 1. Distributed systems.mp4 7.2 MB
  5. 004. Chapter 1. Distributed machine learning systems.mp4 13.2 MB
  6. 005. Chapter 1. What we will learn in this book.mp4 7.6 MB
  7. 006. Chapter 1. Summary.mp4 2.1 MB
  8. 007. Part 2. Patterns of distributed machine learning systems.mp4 9.6 MB
  9. 008. Chapter 2. Data ingestion patterns.mp4 14.8 MB
  10. 009. Chapter 2. The Fashion-MNIST dataset.mp4 13.1 MB
  11. 010. Chapter 2. Batching pattern.mp4 29.3 MB
  12. 011. Chapter 2. Sharding pattern Splitting extremely large datasets among multiple machines.mp4 32.2 MB
  13. 012. Chapter 2. Caching pattern.mp4 25.1 MB
  14. 013. Chapter 2. Answers to exercises.mp4 1.2 MB
  15. 014. Chapter 2. Summary.mp4 2.2 MB
  16. 015. Chapter 3. Distributed training patterns.mp4 13.0 MB
  17. 016. Chapter 3. Parameter server pattern Tagging entities in 8 million YouTube videos.mp4 39.5 MB
  18. 017. Chapter 3. Collective communication pattern.mp4 36.0 MB
  19. 018. Chapter 3. Elasticity and fault-tolerance pattern.mp4 27.1 MB
  20. 019. Chapter 3. Answers to exercises.mp4 2.1 MB
  21. 020. Chapter 3. Summary.mp4 1.9 MB
  22. 021. Chapter 4. Model serving patterns.mp4 12.6 MB
  23. 022. Chapter 4. Replicated services pattern Handling the growing number of serving requests.mp4 28.5 MB
  24. 023. Chapter 4. Sharded services pattern.mp4 27.3 MB
  25. 024. Chapter 4. The event-driven processing pattern.mp4 50.5 MB
  26. 025. Chapter 4. Answers to exercises.mp4 1.8 MB
  27. 026. Chapter 4. Summary.mp4 2.7 MB
  28. 027. Chapter 5. Workflow patterns.mp4 18.8 MB
  29. 028. Chapter 5. Fan-in and fan-out patterns Composing complex machine learning workflows.mp4 34.1 MB
  30. 029. Chapter 5. Synchronous and asynchronous patterns Accelerating workflows with concurrency.mp4 25.4 MB
  31. 030. Chapter 5. Step memoization pattern Skipping redundant workloads via memoized steps.mp4 28.2 MB
  32. 031. Chapter 5. Answers to exercises.mp4 6.6 MB
  33. 032. Chapter 5. Summary.mp4 2.0 MB
  34. 033. Chapter 6. Operation patterns.mp4 18.1 MB
  35. 034. Chapter 6. Scheduling patterns Assigning resources effectively in a shared cluster.mp4 49.7 MB
  36. 035. Chapter 6. Metadata pattern Handle failures appropriately to minimize the negative effect on users.mp4 31.4 MB
  37. 036. Chapter 6. Answers to exercises.mp4 2.6 MB
  38. 037. Chapter 6. Summary.mp4 1.4 MB
  39. 038. Part 3. Building a distributed machine learning workflow.mp4 4.2 MB
  40. 039. Chapter 7. Project overview and system architecture.mp4 18.1 MB
  41. 040. Chapter 7. Data ingestion.mp4 20.7 MB
  42. 041. Chapter 7. Model training.mp4 13.8 MB
  43. 042. Chapter 7. Model serving.mp4 10.2 MB
  44. 043. Chapter 7. End-to-end workflow.mp4 20.3 MB
  45. 044. Chapter 7. Answers to exercises.mp4 965.4 KB
  46. 045. Chapter 7. Summary.mp4 2.1 MB
  47. 046. Chapter 8. Overview of relevant technologies.mp4 25.6 MB
  48. 047. Chapter 8. Kubernetes The distributed container orchestration system.mp4 18.5 MB
  49. 048. Chapter 8. Kubeflow Machine learning workloads on Kubernetes.mp4 24.3 MB
  50. 049. Chapter 8. Argo Workflows Container-native workflow engine.mp4 25.3 MB
  51. 050. Chapter 8. Answers to exercises.mp4 1.3 MB
  52. 051. Chapter 8. Summary.mp4 1.2 MB
  53. 052. Chapter 9. A complete implementation.mp4 24.3 MB
  54. 053. Chapter 9. Model training.mp4 34.7 MB
  55. 054. Chapter 9. Model serving.mp4 20.5 MB
  56. 055. Chapter 9. The end-to-end workflow.mp4 23.3 MB
  57. 056. Chapter 9. Summary.mp4 3.2 MB
  58. Bonus Resources.txt 386 bytes

Discussion