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#Distributed Machine Learning

Showing: 16 courses
Anyscale

Overcoming Distributed ML Challenges with Ray Train

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Unlock efficient distributed ML pipelines with Ray Train. Explore solutions for setup, integration, debugging, fault tolerance, and data processing challenges in scalable machine learning workflows.
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1 Lesons
33 minutes
On-Demand
Free-Video
Linux Foundation

Stream Processing and New Approaches: Edge Processing

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Explore stream processing on the edge for real-time data analysis, enabling rapid anomaly detection and distributed machine learning using open-source software.
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1 Lesons
40 minutes
On-Demand
Free-Video
CNCF [Cloud Native Computing Foundation]

Accelerate Your GenAI Model Inference with Ray and Kubernetes

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Explore serving large GenAI models efficiently using KubeRay on Kubernetes with hardware accelerators. Learn to scale workloads, optimize performance, and reduce costs for production-ready AI inference.
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1 Lesons
28 minutes
On-Demand
Free-Video
TheIACR

Multi-party Computation I - Session 109

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Explore the fundamentals and applications of Multi-party Computation, a cryptographic protocol enabling secure collaborative computations while preserving data privacy.
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1 Lesons
1 hour 6 minutes
On-Demand
Free-Video
IEEE

SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks

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Explore robust algorithms for privacy-preserved federated learning in future networks, focusing on explainable and secure data collaboration techniques.
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1 Lesons
15 minutes
On-Demand
Free-Video
USENIX

Oort - Efficient Federated Learning via Guided Participant Selection

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Efficient federated learning system that improves model training and testing by intelligently selecting participants based on data utility and device capabilities, enhancing accuracy and performance.
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14 Lesons
16 minutes
On-Demand
Free-Video
USENIX

KungFu - Making Training in Distributed Machine Learning Adaptive

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KungFu: adaptive distributed machine learning library for TensorFlow. Enables real-time parameter tuning using high-level policies, efficient monitoring, and asynchronous communication for improved training performance.
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17 Lesons
20 minutes
On-Demand
Free-Video
USENIX

Scaling Distributed Machine Learning with the Parameter Server

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Explore a framework for distributed machine learning using parameter servers, enabling scalable processing of petabyte-scale data with billions of examples and parameters across various algorithms.
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1 Lesons
24 minutes
On-Demand
Free-Video
Devoxx

Distributed Machine Learning 101 Using Apache Spark from a Browser

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Explore introductory machine learning concepts and their application at scale using Apache Spark, with hands-on examples in interactive notebooks for real-world distributed data processing.
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1 Lesons
2 hours 39 minutes
On-Demand
Free-Video
TheIACR

PPML 2020 - Welcome and Invited Talk - Contributed Talks

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Explore cutting-edge research in privacy-preserving machine learning, including split learning, secure inference, fairness certification, crypto-oriented neural architectures, and privacy-preserving decision trees.
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1 Lesons
1 hour 24 minutes
On-Demand
Free-Video
USENIX

Accelerating Distributed MoE Training and Inference with Lina

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Explore Lina, an innovative system for accelerating distributed Mixture of Experts training and inference, addressing all-to-all communication bottlenecks in large-scale AI models.
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1 Lesons
20 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Federated Learning in Production: Enabling AI Training with Data Privacy

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Explore federated learning's applications, benefits, and implementation requirements for AI training on edge devices with data privacy.
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1 Lesons
25 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Federated Learning in Production: Enabling AI Training with Data Privacy

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Explore federated learning's applications, benefits, and implementation requirements for AI training on edge devices with data privacy.
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1 Lesons
25 minutes
On-Demand
Free-Video
USENIX

Learning and Unlearning Your Data in Federated Settings

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Explore federated learning and unlearning approaches for collaborative AI model training while preserving data privacy. Analyze methods for removing data inputs in distributed settings to comply with regulations.
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1 Lesons
15 minutes
On-Demand
Free-Video
USENIX

Conspirator - SmartNIC-Aided Control Plane for Distributed ML Workloads

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Innovative control plane design using SmartNICs to optimize distributed ML workloads, reducing bottlenecks and improving resource utilization for enhanced performance and efficiency.
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1 Lesons
18 minutes
On-Demand
Free-Video
HOTI - Hot Interconnects Symposium

ASTRA-sim and Chakra - Co-design Exploration for Distributed Machine Learning Platforms

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Explore co-design methodologies for distributed ML platforms using ASTRA-sim and Chakra frameworks, focusing on system optimization and performance analysis.
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1 Lesons
1 hour 58 minutes
On-Demand
Free-Video