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Anyscale
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anyscale
107 Decks
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Scaling and Unifying SciKit Learn and Spark Pipelines using Ray (Raghu Ganti, IBM)
anyscale
PRO
0
230
Fusion Computing at Ant Group (Dr. Charles He, Ant Group)
anyscale
PRO
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260
Anomaly Detection on Remote Sensing with Ray + Horovod (Linsong Chu, IBM Research)
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PRO
0
180
A Deep Dive into Ray’s Scheduling Policy (Alex Wu, Anyscale)
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PRO
0
270
Large Scale Data Loading and Data Preprocessing with Ray (Wei Chen, NVIDIA)
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PRO
0
330
Applying Ray and RLlib to Real-life Industrial Use Cases (Edward Junprung & Sahar Esmaeilzadeh, Pathmind)
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PRO
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450
Collective-on-Ray: High-performance Collective Communication for Distributed Machine Learning on Ray (Hao Zhang, UC Berkeley)
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PRO
0
170
Mars-on-Ray: Accelerating Large-scale Tensor and DataFrame Workloads (Chris Qin, Alibaba Cloud)
anyscale
PRO
0
230
Machine Learning and Microbiology in the Cloud Through Ray (Stanley Bishop, Drift Biotechnologies)
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PRO
0
130
A Growing Ecosystem of Scalable ML Libraries on Ray (Amog Kamsetty, Anyscale)
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PRO
0
120
Powering Open Data Hub with Ray (Erik Erlandson, Red Hat, AI Center of Excellence)
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PRO
0
240
Using RLLib in an Enterprise Scale Reinforcement Learning Solution (Jeroen Bédorf & Ishaan Sood, minds.ai)
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PRO
0
200
Software 2.0 Needs Data 2.0: A New Way of Storing and Managing Data for Efficient Deep Learning (Davit Buniatyan, Activeloop)
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PRO
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130
Introducing Amazon SageMaker Kubeflow Reinforcement Learning Pipelines for Robotics (Sahika Genc, Amazon)
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PRO
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410
Simplify Big Data & AI on Spark and Ray with MLSQL (Dong Li, Kyligence)
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PRO
0
140
Application of Online Resource Allocation Based on Ray (Fang Fengbin, Ant Group)
anyscale
PRO
0
120
Towards Building a Responsible Data Economy (Dawn Song, UC Berkeley)
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PRO
0
200
JAX: Accelerated Machine Learning Research via Composable Function Transformations in Python (Matt Johnson, Google Brain)
anyscale
PRO
0
210
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