MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 57m | Size: 1.76 GB
Modern ML and AI applications require a lot of compute power, which usually means distribution over a cluster of machines, as well as management of distributed state, such as the model parameters being trained. Ray, a high-performance distributed execution framework developed by UC Berkeley's RISELab, is targeted at large-scale machine learning and reinforcement learning applications. Ray's features make it suitable for any Python-based application that needs cluster-wide scalability.
Join us for this edition of Meet the Expert with Dean Wampler to see how Ray meets the needs of ML/AI applications-without requiring the skills and DevOps effort typically required for distributed computing. You'll learn how Ray enables distribution of Python applications over a cluster and explore examples of ML libraries that use Ray, allowing data scientists to do their work at scale without a lot of programming.
O'Reilly Meet the Expert explores emerging business and technology topics and ideas through a series of one-hour interactive events. You'll engage in a live conversation with experts, sharing your questions and ideas while hearing their unique perspectives, insights, fears, and predictions.
http://rapidgator.net/file/44a6f5b7eef10d60a0dded1fdc421aa0/Meet_the_Expert_-_Dean_Wampler_on_Scaling_ML_AI_Applications_with_Ray.part2_2.rar.html
or
https://uploadgig.com/file/download/fe311Df77eBbf17C/Meet_the_Expert_-_Dean_Wampler_on_Scaling_ML_AI_Applications_with_Ray.part1_2.rar
https://uploadgig.com/file/download/0aA6C857117958bE/Meet_the_Expert_-_Dean_Wampler_on_Scaling_ML_AI_Applications_with_Ray.part2_2.rar