July 2020 Summaries
4 posts from Anyscale
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Yesterday, Anyscale hosted its latest installment of Anyscale Academy, which focused on Ray Tune and Ray Serve. The session's video is now available on the Anyscale YouTube channel for viewing by interested parties. A wealth of additional resources, including supporting notebooks and code, are also provided through the Anyscale Academy GitHub repository. Furthermore, attendees are encouraged to check out upcoming events, such as Ray Summit Connect: MLOps in the Real World, which can be found at anyscale.com/events.
Jul 23, 2020
61 words in the original blog post.
Anyscale has been recognized as one of Forbes' top 50 most promising Artificial Intelligence companies, specifically for its role in helping software developers create machine-learning apps. The company aims to enable rapid time-to-market and faster iterations across the entire AI lifecycle through its partnership with Ray, allowing companies to benefit from this collaboration.
Jul 16, 2020
53 words in the original blog post.
Machine learning (ML) platform designers are facing challenges in managing the ML lifecycle as machine learning becomes increasingly prevalent in companies. Many teams start by giving data scientists Jupyter notebooks backed by GPU instances, but this approach breaks down with growing complexity and number of deployments. As a result, more teams are looking for end-to-end ML platforms. Several cloud providers and startups offer these platforms, including AWS (SageMaker), Azure (Machine Learning Studio), Databricks (MLflow), Google (Cloud AI Platform), and others. Ray is a general purpose distributed computing platform that can be used to easily scale existing Python libraries and applications, making it useful for building ML tools and platforms.
Jul 13, 2020
1,517 words in the original blog post.
The videos and slides from the third Ray Summit Connect event are now available for viewing. The event featured talks on scalable reinforcement learning for TensorFlow, PyTorch, and other frameworks, as well as a panel discussion on connecting RL to simulation software. Additionally, sessions were held on building and deploying RLlib models on Amazon SageMaker RL and more.
Jul 08, 2020
123 words in the original blog post.