Oreilly - Distributed Machine Learning Patterns, Video Edition --> [ FreeCourseWeb ]
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Oreilly - Distributed Machine Learning Patterns, Video Edition --> [ FreeCourseWeb ]
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Torrent File Content (58 files)
[ FreeCourseWeb.com ] Oreilly - Distributed Machine Learning Patterns, Video Edition
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183 bytes
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001. Part 1. Basic concepts and background.mp4 -
001. Part 1. Basic concepts and background.mp4 -
2.4 MB
002. Chapter 1. Introduction to distributed machine learning systems.mp4 -
27.89 MB
003. Chapter 1. Distributed systems.mp4 -
7.24 MB
004. Chapter 1. Distributed machine learning systems.mp4 -
13.22 MB
005. Chapter 1. What we will learn in this book.mp4 -
7.56 MB
006. Chapter 1. Summary.mp4 -
2.08 MB
007. Part 2. Patterns of distributed machine learning systems.mp4 -
9.56 MB
008. Chapter 2. Data ingestion patterns.mp4 -
14.8 MB
009. Chapter 2. The Fashion-MNIST dataset.mp4 -
13.15 MB
010. Chapter 2. Batching pattern.mp4 -
29.32 MB
011. Chapter 2. Sharding pattern Splitting extremely large datasets among multiple machines.mp4 -
32.21 MB
012. Chapter 2. Caching pattern.mp4 -
25.12 MB
013. Chapter 2. Answers to exercises.mp4 -
1.16 MB
014. Chapter 2. Summary.mp4 -
2.23 MB
015. Chapter 3. Distributed training patterns.mp4 -
13.02 MB
016. Chapter 3. Parameter server pattern Tagging entities in 8 million YouTube videos.mp4 -
39.51 MB
017. Chapter 3. Collective communication pattern.mp4 -
36 MB
018. Chapter 3. Elasticity and fault-tolerance pattern.mp4 -
27.12 MB
019. Chapter 3. Answers to exercises.mp4 -
2.11 MB
020. Chapter 3. Summary.mp4 -
1.94 MB
021. Chapter 4. Model serving patterns.mp4 -
12.59 MB
022. Chapter 4. Replicated services pattern Handling the growing number of serving requests.mp4 -
28.48 MB
023. Chapter 4. Sharded services pattern.mp4 -
27.28 MB
024. Chapter 4. The event-driven processing pattern.mp4 -
50.45 MB
025. Chapter 4. Answers to exercises.mp4 -
1.78 MB
026. Chapter 4. Summary.mp4 -
2.65 MB
027. Chapter 5. Workflow patterns.mp4 -
18.76 MB
028. Chapter 5. Fan-in and fan-out patterns Composing complex machine learning workflows.mp4 -
34.13 MB
029. Chapter 5. Synchronous and asynchronous patterns Accelerating workflows with concurrency.mp4 -
25.38 MB
030. Chapter 5. Step memoization pattern Skipping redundant workloads via memoized steps.mp4 -
28.17 MB
031. Chapter 5. Answers to exercises.mp4 -
6.63 MB
032. Chapter 5. Summary.mp4 -
2.03 MB
033. Chapter 6. Operation patterns.mp4 -
18.13 MB
034. Chapter 6. Scheduling patterns Assigning resources effectively in a shared cluster.mp4 -
49.75 MB
035. Chapter 6. Metadata pattern Handle failures appropriately to minimize the negative effect on users.mp4 -
31.43 MB
036. Chapter 6. Answers to exercises.mp4 -
2.56 MB
037. Chapter 6. Summary.mp4 -
1.41 MB
038. Part 3. Building a distributed machine learning workflow.mp4 -
4.19 MB
039. Chapter 7. Project overview and system architecture.mp4 -
18.07 MB
040. Chapter 7. Data ingestion.mp4 -
20.7 MB
041. Chapter 7. Model training.mp4 -
13.83 MB
042. Chapter 7. Model serving.mp4 -
10.15 MB
043. Chapter 7. End-to-end workflow.mp4 -
20.32 MB
044. Chapter 7. Answers to exercises.mp4 -
965.37 KB
045. Chapter 7. Summary.mp4 -
2.09 MB
046. Chapter 8. Overview of relevant technologies.mp4 -
25.59 MB
047. Chapter 8. Kubernetes The distributed container orchestration system.mp4 -
18.53 MB
048. Chapter 8. Kubeflow Machine learning workloads on Kubernetes.mp4 -
24.27 MB
049. Chapter 8. Argo Workflows Container-native workflow engine.mp4 -
25.28 MB
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