Oreilly - Distributed Machine Learning Patterns, Video Edition

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Oreilly - Distributed Machine Learning Patterns, Video Edition

Torrent Contents Size: 941.8 MB

Oreilly - Distributed Machine Learning Patterns, Video Edition
▼ show more 43 files
001. Part 1. Basic concepts and background.mp4
MP4
2.4 MB
002. Chapter 1. Introduction to distributed machine learning systems.mp4
MP4
27.9 MB
003. Chapter 1. Distributed systems.mp4
MP4
7.2 MB
004. Chapter 1. Distributed machine learning systems.mp4
MP4
13.2 MB
005. Chapter 1. What we will learn in this book.mp4
MP4
7.6 MB
006. Chapter 1. Summary.mp4
MP4
2.1 MB
007. Part 2. Patterns of distributed machine learning systems.mp4
MP4
9.6 MB
008. Chapter 2. Data ingestion patterns.mp4
MP4
14.8 MB
009. Chapter 2. The Fashion-MNIST dataset.mp4
MP4
13.1 MB
010. Chapter 2. Batching pattern.mp4
MP4
29.3 MB
011. Chapter 2. Sharding pattern Splitting extremely large datasets among multiple machines.mp4
MP4
32.2 MB
012. Chapter 2. Caching pattern.mp4
MP4
25.1 MB
013. Chapter 2. Answers to exercises.mp4
MP4
1.2 MB
014. Chapter 2. Summary.mp4
MP4
2.2 MB
015. Chapter 3. Distributed training patterns.mp4
MP4
13 MB
016. Chapter 3. Parameter server pattern Tagging entities in 8 million YouTube videos.mp4
MP4
39.5 MB
017. Chapter 3. Collective communication pattern.mp4
MP4
36 MB
018. Chapter 3. Elasticity and fault-tolerance pattern.mp4
MP4
27.1 MB
019. Chapter 3. Answers to exercises.mp4
MP4
2.1 MB
020. Chapter 3. Summary.mp4
MP4
1.9 MB
021. Chapter 4. Model serving patterns.mp4
MP4
12.6 MB
022. Chapter 4. Replicated services pattern Handling the growing number of serving requests.mp4
MP4
28.5 MB
023. Chapter 4. Sharded services pattern.mp4
MP4
27.3 MB
024. Chapter 4. The event-driven processing pattern.mp4
MP4
50.5 MB
025. Chapter 4. Answers to exercises.mp4
MP4
1.8 MB
026. Chapter 4. Summary.mp4
MP4
2.7 MB
027. Chapter 5. Workflow patterns.mp4
MP4
18.8 MB
028. Chapter 5. Fan-in and fan-out patterns Composing complex machine learning workflows.mp4
MP4
34.1 MB
029. Chapter 5. Synchronous and asynchronous patterns Accelerating workflows with concurrency.mp4
MP4
25.4 MB
030. Chapter 5. Step memoization pattern Skipping redundant workloads via memoized steps.mp4
MP4
28.2 MB
031. Chapter 5. Answers to exercises.mp4
MP4
6.6 MB
032. Chapter 5. Summary.mp4
MP4
2 MB
033. Chapter 6. Operation patterns.mp4
MP4
18.1 MB
034. Chapter 6. Scheduling patterns Assigning resources effectively in a shared cluster.mp4
MP4
49.7 MB
035. Chapter 6. Metadata pattern Handle failures appropriately to minimize the negative effect on users.mp4
MP4
31.4 MB
036. Chapter 6. Answers to exercises.mp4
MP4
2.6 MB
037. Chapter 6. Summary.mp4
MP4
1.4 MB
038. Part 3. Building a distributed machine learning workflow.mp4
MP4
4.2 MB
039. Chapter 7. Project overview and system architecture.mp4
MP4
18.1 MB
040. Chapter 7. Data ingestion.mp4
MP4
20.7 MB
041. Chapter 7. Model training.mp4
MP4
13.8 MB
042. Chapter 7. Model serving.mp4
MP4
10.2 MB
043. Chapter 7. End-to-end workflow.mp4
MP4
20.3 MB
044. Chapter 7. Answers to exercises.mp4
MP4
965.4 KB
045. Chapter 7. Summary.mp4
MP4
2.1 MB
046. Chapter 8. Overview of relevant technologies.mp4
MP4
25.6 MB
047. Chapter 8. Kubernetes The distributed container orchestration system.mp4
MP4
18.5 MB
048. Chapter 8. Kubeflow Machine learning workloads on Kubernetes.mp4
MP4
24.3 MB
049. Chapter 8. Argo Workflows Container-native workflow engine.mp4
MP4
25.3 MB
050. Chapter 8. Answers to exercises.mp4
MP4
1.3 MB
051. Chapter 8. Summary.mp4
MP4
1.2 MB
052. Chapter 9. A complete implementation.mp4
MP4
24.3 MB
053. Chapter 9. Model training.mp4
MP4
34.7 MB
054. Chapter 9. Model serving.mp4
MP4
20.5 MB
055. Chapter 9. The end-to-end workflow.mp4
MP4
23.3 MB
056. Chapter 9. Summary.mp4
MP4
3.2 MB
Bonus Resources.txt
TXT
409.6 B
Get Bonus Downloads Here.url
URL
204.8 B

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