FreeCourseWeb com Oreilly Distributed Machine Learning Patterns Video Edition

FreeCourseWeb com Oreilly Distributed Machine Learning Patterns Video Edition

Name	[ FreeCourseWeb.com ] Oreilly - Distributed Machine Learning Patterns, Video Edition	DOWNLOAD Copy Link
Total Size	987.6 MB
Total Files	58
Last Seen	2025-01-18 23:49
Hash	1581E53F329C9DBAF6283E6BE36D42995E54AAB9

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001. Part 1. Basic concepts and background.mp4	2.5 MB
002. Chapter 1. Introduction to distributed machine learning systems.mp4	29.2 MB
003. Chapter 1. Distributed systems.mp4	7.6 MB
004. Chapter 1. Distributed machine learning systems.mp4	13.9 MB
005. Chapter 1. What we will learn in this book.mp4	7.9 MB
006. Chapter 1. Summary.mp4	2.2 MB
007. Part 2. Patterns of distributed machine learning systems.mp4	10.0 MB
008. Chapter 2. Data ingestion patterns.mp4	15.5 MB
009. Chapter 2. The Fashion-MNIST dataset.mp4	13.8 MB
010. Chapter 2. Batching pattern.mp4	30.7 MB
011. Chapter 2. Sharding pattern Splitting extremely large datasets among multiple machines.mp4	33.8 MB
012. Chapter 2. Caching pattern.mp4	26.3 MB
013. Chapter 2. Answers to exercises.mp4	1.2 MB
014. Chapter 2. Summary.mp4	2.3 MB
015. Chapter 3. Distributed training patterns.mp4	13.7 MB
016. Chapter 3. Parameter server pattern Tagging entities in 8 million YouTube videos.mp4	41.4 MB
017. Chapter 3. Collective communication pattern.mp4	37.7 MB
018. Chapter 3. Elasticity and fault-tolerance pattern.mp4	28.4 MB
019. Chapter 3. Answers to exercises.mp4	2.2 MB
020. Chapter 3. Summary.mp4	2.0 MB
021. Chapter 4. Model serving patterns.mp4	13.2 MB
022. Chapter 4. Replicated services pattern Handling the growing number of serving requests.mp4	29.9 MB
023. Chapter 4. Sharded services pattern.mp4	28.6 MB
024. Chapter 4. The event-driven processing pattern.mp4	52.9 MB
025. Chapter 4. Answers to exercises.mp4	1.9 MB
026. Chapter 4. Summary.mp4	2.8 MB
027. Chapter 5. Workflow patterns.mp4	19.7 MB
028. Chapter 5. Fan-in and fan-out patterns Composing complex machine learning workflows.mp4	35.8 MB
029. Chapter 5. Synchronous and asynchronous patterns Accelerating workflows with concurrency.mp4	26.6 MB
030. Chapter 5. Step memoization pattern Skipping redundant workloads via memoized steps.mp4	29.5 MB
031. Chapter 5. Answers to exercises.mp4	6.9 MB
032. Chapter 5. Summary.mp4	2.1 MB
033. Chapter 6. Operation patterns.mp4	19.0 MB
034. Chapter 6. Scheduling patterns Assigning resources effectively in a shared cluster.mp4	52.2 MB
035. Chapter 6. Metadata pattern Handle failures appropriately to minimize the negative effect on users.mp4	33.0 MB
036. Chapter 6. Answers to exercises.mp4	2.7 MB
037. Chapter 6. Summary.mp4	1.5 MB
038. Part 3. Building a distributed machine learning workflow.mp4	4.4 MB
039. Chapter 7. Project overview and system architecture.mp4	18.9 MB
040. Chapter 7. Data ingestion.mp4	21.7 MB
041. Chapter 7. Model training.mp4	14.5 MB
042. Chapter 7. Model serving.mp4	10.6 MB
043. Chapter 7. End-to-end workflow.mp4	21.3 MB
044. Chapter 7. Answers to exercises.mp4	988.5 KB
045. Chapter 7. Summary.mp4	2.2 MB
046. Chapter 8. Overview of relevant technologies.mp4	26.8 MB
047. Chapter 8. Kubernetes The distributed container orchestration system.mp4	19.4 MB
048. Chapter 8. Kubeflow Machine learning workloads on Kubernetes.mp4	25.4 MB
049. Chapter 8. Argo Workflows Container-native workflow engine.mp4	26.5 MB
050. Chapter 8. Answers to exercises.mp4	1.3 MB
051. Chapter 8. Summary.mp4	1.3 MB
052. Chapter 9. A complete implementation.mp4	25.5 MB
053. Chapter 9. Model training.mp4	36.4 MB
054. Chapter 9. Model serving.mp4	21.5 MB
055. Chapter 9. The end-to-end workflow.mp4	24.4 MB
056. Chapter 9. Summary.mp4	3.4 MB
Bonus Resources.txt	0.4 KB
Total files 58